deepfates
/
hunyuan-the-matrix-trilogy
Hunyuan-Video model finetuned on The Matrix Trilogy (1999). Trigger word is "THMTR". Use "A video in the style of THMTR, THMTR" at the beginning of your prompt for best results.
- Public
- 108 runs
-
H100
- Fine-tune
Prediction
deepfates/hunyuan-the-matrix-trilogy:e84c3dd2ID9n7b1gxzdsrma0cmjps95sxx00StatusSucceededSourceAPIHardwareH100Total durationCreatedInput
- crf
- 19
- seed
- 12345
- steps
- 50
- width
- 640
- height
- 360
- prompt
- A video in the style of THMTR, THMTR The video clip depicts a detailed portrait of a woman's face. She has fair skin and bright, intense blue eyes that gaze directly ahead. Her hair is dark and wavy, cascading down her shoulders in a curly pattern. She is dressed in a dark dress with a square neckline adorned with intricate metallic accents. The dress has a detailed, almost mosaic-like pattern, suggesting a ceremonial or formal attire. The woman's expression is stoic and serious, conveying a sense of determination or resolve. The background is dark, contrasting with the intricate details of her dress and the brightness of her eyes. The lighting is soft and diffused, casting a warm glow on
- lora_url
- scheduler
- DPMSolverMultistepScheduler
- flow_shift
- 9
- frame_rate
- 16
- num_frames
- 66
- enhance_end
- 1
- enhance_start
- 0
- force_offload
- lora_strength
- 1
- enhance_double
- enhance_single
- enhance_weight
- 0.3
- guidance_scale
- 6
- denoise_strength
- 1
{ "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a detailed portrait of a woman's face. She has fair skin and bright, intense blue eyes that gaze directly ahead. Her hair is dark and wavy, cascading down her shoulders in a curly pattern. She is dressed in a dark dress with a square neckline adorned with intricate metallic accents. The dress has a detailed, almost mosaic-like pattern, suggesting a ceremonial or formal attire.\nThe woman's expression is stoic and serious, conveying a sense of determination or resolve. The background is dark, contrasting with the intricate details of her dress and the brightness of her eyes. The lighting is soft and diffused, casting a warm glow on", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 16, "num_frames": 66, "enhance_end": 1, "enhance_start": 0, "force_offload": true, "lora_strength": 1, "enhance_double": true, "enhance_single": true, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", { input: { crf: 19, seed: 12345, steps: 50, width: 640, height: 360, prompt: "A video in the style of THMTR, THMTR The video clip depicts a detailed portrait of a woman's face. She has fair skin and bright, intense blue eyes that gaze directly ahead. Her hair is dark and wavy, cascading down her shoulders in a curly pattern. She is dressed in a dark dress with a square neckline adorned with intricate metallic accents. The dress has a detailed, almost mosaic-like pattern, suggesting a ceremonial or formal attire.\nThe woman's expression is stoic and serious, conveying a sense of determination or resolve. The background is dark, contrasting with the intricate details of her dress and the brightness of her eyes. The lighting is soft and diffused, casting a warm glow on", lora_url: "", scheduler: "DPMSolverMultistepScheduler", flow_shift: 9, frame_rate: 16, num_frames: 66, enhance_end: 1, enhance_start: 0, force_offload: true, lora_strength: 1, enhance_double: true, enhance_single: true, enhance_weight: 0.3, guidance_scale: 6, denoise_strength: 1 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", input={ "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a detailed portrait of a woman's face. She has fair skin and bright, intense blue eyes that gaze directly ahead. Her hair is dark and wavy, cascading down her shoulders in a curly pattern. She is dressed in a dark dress with a square neckline adorned with intricate metallic accents. The dress has a detailed, almost mosaic-like pattern, suggesting a ceremonial or formal attire.\nThe woman's expression is stoic and serious, conveying a sense of determination or resolve. The background is dark, contrasting with the intricate details of her dress and the brightness of her eyes. The lighting is soft and diffused, casting a warm glow on", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 16, "num_frames": 66, "enhance_end": 1, "enhance_start": 0, "force_offload": True, "lora_strength": 1, "enhance_double": True, "enhance_single": True, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", "input": { "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a detailed portrait of a woman\'s face. She has fair skin and bright, intense blue eyes that gaze directly ahead. Her hair is dark and wavy, cascading down her shoulders in a curly pattern. She is dressed in a dark dress with a square neckline adorned with intricate metallic accents. The dress has a detailed, almost mosaic-like pattern, suggesting a ceremonial or formal attire.\\nThe woman\'s expression is stoic and serious, conveying a sense of determination or resolve. The background is dark, contrasting with the intricate details of her dress and the brightness of her eyes. The lighting is soft and diffused, casting a warm glow on", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 16, "num_frames": 66, "enhance_end": 1, "enhance_start": 0, "force_offload": true, "lora_strength": 1, "enhance_double": true, "enhance_single": true, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-24T00:29:37.158743Z", "created_at": "2025-01-24T00:25:07.182000Z", "data_removed": false, "error": null, "id": "9n7b1gxzdsrma0cmjps95sxx00", "input": { "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a detailed portrait of a woman's face. She has fair skin and bright, intense blue eyes that gaze directly ahead. Her hair is dark and wavy, cascading down her shoulders in a curly pattern. She is dressed in a dark dress with a square neckline adorned with intricate metallic accents. The dress has a detailed, almost mosaic-like pattern, suggesting a ceremonial or formal attire.\nThe woman's expression is stoic and serious, conveying a sense of determination or resolve. The background is dark, contrasting with the intricate details of her dress and the brightness of her eyes. The lighting is soft and diffused, casting a warm glow on", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 16, "num_frames": 66, "enhance_end": 1, "enhance_start": 0, "force_offload": true, "lora_strength": 1, "enhance_double": true, "enhance_single": true, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 }, "logs": "Seed set to: 12345\n⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements\n⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements\nChecking inputs\n====================================\nChecking weights\n✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae\n✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models\n====================================\nRunning workflow\n[ComfyUI] got prompt\nExecuting node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode\n[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 146\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77\n[ComfyUI] Input (height, width, video_length) = (368, 640, 65)\n[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps\n[ComfyUI]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:53, 2.32s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:37, 2.03s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:41, 2.15s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.21s/it]\n[ComfyUI] 10%|█ | 5/50 [00:11<01:40, 2.24s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.26s/it]\n[ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.28s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.28s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.29s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.30s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.30s/it]\n[ComfyUI] 26%|██▌ | 13/50 [00:29<01:25, 2.30s/it]\n[ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.30s/it]\n[ComfyUI] 30%|███ | 15/50 [00:34<01:20, 2.30s/it]\n[ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it]\n[ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.30s/it]\n[ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.30s/it]\n[ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it]\n[ComfyUI] 40%|████ | 20/50 [00:45<01:09, 2.30s/it]\n[ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it]\n[ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it]\n[ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it]\n[ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it]\n[ComfyUI] 50%|█████ | 25/50 [00:57<00:57, 2.30s/it]\n[ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it]\n[ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.30s/it]\n[ComfyUI] 56%|█████▌ | 28/50 [01:04<00:50, 2.30s/it]\n[ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it]\n[ComfyUI] 60%|██████ | 30/50 [01:08<00:46, 2.30s/it]\n[ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.30s/it]\n[ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it]\n[ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it]\n[ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it]\n[ComfyUI] 70%|███████ | 35/50 [01:20<00:34, 2.30s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:27<00:27, 2.30s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/it]\n[ComfyUI] 80%|████████ | 40/50 [01:31<00:23, 2.30s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.30s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.30s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it]\n[ComfyUI] 90%|█████████ | 45/50 [01:43<00:11, 2.30s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:50<00:04, 2.30s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it]\n[ComfyUI] Allocated memory: memory=12.300 GB\n[ComfyUI] Max allocated memory: max_memory=15.099 GB\n[ComfyUI] Max reserved memory: max_reserved=16.312 GB\nExecuting node 5, title: HunyuanVideo Decode, class type: HyVideoDecode\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.48s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.25s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.29s/it]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.70it/s]\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.53it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.00it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.92it/s]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\nExecuting node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 65.02it/s]\n[ComfyUI] Prompt executed in 133.12 seconds\noutputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}}\n====================================\nHunyuanVideo_00001.png\nHunyuanVideo_00001.mp4", "metrics": { "predict_time": 139.372596184, "total_time": 269.976743 }, "output": "https://replicate.delivery/xezq/Yw7ucdrnlAqxH1i39KCXdHwc99Zve4MeCa0aybjF5BxxDJIUA/HunyuanVideo_00001.mp4", "started_at": "2025-01-24T00:27:17.786146Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-atqtus2x5dlfkn3xuwiilctpoqxum3ouzgpmwtoit3x2mallcrka", "get": "https://api.replicate.com/v1/predictions/9n7b1gxzdsrma0cmjps95sxx00", "cancel": "https://api.replicate.com/v1/predictions/9n7b1gxzdsrma0cmjps95sxx00/cancel" }, "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9" }Generated inSeed set to: 12345 ⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements ⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements Checking inputs ==================================== Checking weights ✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae ✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models ==================================== Running workflow [ComfyUI] got prompt Executing node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode [ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 146 [ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77 [ComfyUI] Input (height, width, video_length) = (368, 640, 65) [ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler [ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps [ComfyUI] [ComfyUI] 0%| | 0/50 [00:00<?, ?it/s] [ComfyUI] 2%|▏ | 1/50 [00:02<01:53, 2.32s/it] [ComfyUI] 4%|▍ | 2/50 [00:04<01:37, 2.03s/it] [ComfyUI] 6%|▌ | 3/50 [00:06<01:41, 2.15s/it] [ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.21s/it] [ComfyUI] 10%|█ | 5/50 [00:11<01:40, 2.24s/it] [ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.26s/it] [ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.28s/it] [ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.28s/it] [ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.29s/it] [ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it] [ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.30s/it] [ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.30s/it] [ComfyUI] 26%|██▌ | 13/50 [00:29<01:25, 2.30s/it] [ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.30s/it] [ComfyUI] 30%|███ | 15/50 [00:34<01:20, 2.30s/it] [ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it] [ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.30s/it] [ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.30s/it] [ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it] [ComfyUI] 40%|████ | 20/50 [00:45<01:09, 2.30s/it] [ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it] [ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it] [ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it] [ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it] [ComfyUI] 50%|█████ | 25/50 [00:57<00:57, 2.30s/it] [ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it] [ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.30s/it] [ComfyUI] 56%|█████▌ | 28/50 [01:04<00:50, 2.30s/it] [ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it] [ComfyUI] 60%|██████ | 30/50 [01:08<00:46, 2.30s/it] [ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.30s/it] [ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it] [ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it] [ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it] [ComfyUI] 70%|███████ | 35/50 [01:20<00:34, 2.30s/it] [ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it] [ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it] [ComfyUI] 76%|███████▌ | 38/50 [01:27<00:27, 2.30s/it] [ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/it] [ComfyUI] 80%|████████ | 40/50 [01:31<00:23, 2.30s/it] [ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.30s/it] [ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.30s/it] [ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it] [ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it] [ComfyUI] 90%|█████████ | 45/50 [01:43<00:11, 2.30s/it] [ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it] [ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it] [ComfyUI] 96%|█████████▌| 48/50 [01:50<00:04, 2.30s/it] [ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it] [ComfyUI] Allocated memory: memory=12.300 GB [ComfyUI] Max allocated memory: max_memory=15.099 GB [ComfyUI] Max reserved memory: max_reserved=16.312 GB Executing node 5, title: HunyuanVideo Decode, class type: HyVideoDecode [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.48s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.25s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.29s/it] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.70it/s] [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.53it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.00it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.92it/s] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 65.02it/s] [ComfyUI] Prompt executed in 133.12 seconds outputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}} ==================================== HunyuanVideo_00001.png HunyuanVideo_00001.mp4Prediction
deepfates/hunyuan-the-matrix-trilogy:e84c3dd2IDw7j2vac1v1rm80cmjpf8kpdzawStatusSucceededSourceAPIHardwareH100Total durationCreatedInput
- crf
- 19
- seed
- 12345
- steps
- 50
- width
- 640
- height
- 360
- prompt
- A video in the style of THMTR, THMTR The video clip depicts a serene and picturesque snow-covered landscape. The scene is set in a hilly area with dense snow covering the ground, trees, and rocks. A man dressed in a dark coat and hat is walking along a snowy path, carrying a briefcase. The path is surrounded by large boulders and snow-covered trees, creating a stark contrast between the whiteness of the snow and the dark clothes of the man. The atmosphere is calm and peaceful, with a soft blue light illuminating the scene, suggesting that it might be early morning or late evening. The sound of crunching snow beneath the man's feet can be heard as he makes
- lora_url
- scheduler
- DPMSolverMultistepScheduler
- flow_shift
- 9
- frame_rate
- 16
- num_frames
- 66
- enhance_end
- 1
- enhance_start
- 0
- force_offload
- lora_strength
- 1
- enhance_double
- enhance_single
- enhance_weight
- 0.3
- guidance_scale
- 6
- denoise_strength
- 1
{ "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a serene and picturesque snow-covered landscape. The scene is set in a hilly area with dense snow covering the ground, trees, and rocks. A man dressed in a dark coat and hat is walking along a snowy path, carrying a briefcase. The path is surrounded by large boulders and snow-covered trees, creating a stark contrast between the whiteness of the snow and the dark clothes of the man.\nThe atmosphere is calm and peaceful, with a soft blue light illuminating the scene, suggesting that it might be early morning or late evening. The sound of crunching snow beneath the man's feet can be heard as he makes", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 16, "num_frames": 66, "enhance_end": 1, "enhance_start": 0, "force_offload": true, "lora_strength": 1, "enhance_double": true, "enhance_single": true, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", { input: { crf: 19, seed: 12345, steps: 50, width: 640, height: 360, prompt: "A video in the style of THMTR, THMTR The video clip depicts a serene and picturesque snow-covered landscape. The scene is set in a hilly area with dense snow covering the ground, trees, and rocks. A man dressed in a dark coat and hat is walking along a snowy path, carrying a briefcase. The path is surrounded by large boulders and snow-covered trees, creating a stark contrast between the whiteness of the snow and the dark clothes of the man.\nThe atmosphere is calm and peaceful, with a soft blue light illuminating the scene, suggesting that it might be early morning or late evening. The sound of crunching snow beneath the man's feet can be heard as he makes", lora_url: "", scheduler: "DPMSolverMultistepScheduler", flow_shift: 9, frame_rate: 16, num_frames: 66, enhance_end: 1, enhance_start: 0, force_offload: true, lora_strength: 1, enhance_double: true, enhance_single: true, enhance_weight: 0.3, guidance_scale: 6, denoise_strength: 1 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", input={ "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a serene and picturesque snow-covered landscape. The scene is set in a hilly area with dense snow covering the ground, trees, and rocks. A man dressed in a dark coat and hat is walking along a snowy path, carrying a briefcase. The path is surrounded by large boulders and snow-covered trees, creating a stark contrast between the whiteness of the snow and the dark clothes of the man.\nThe atmosphere is calm and peaceful, with a soft blue light illuminating the scene, suggesting that it might be early morning or late evening. The sound of crunching snow beneath the man's feet can be heard as he makes", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 16, "num_frames": 66, "enhance_end": 1, "enhance_start": 0, "force_offload": True, "lora_strength": 1, "enhance_double": True, "enhance_single": True, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", "input": { "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a serene and picturesque snow-covered landscape. The scene is set in a hilly area with dense snow covering the ground, trees, and rocks. A man dressed in a dark coat and hat is walking along a snowy path, carrying a briefcase. The path is surrounded by large boulders and snow-covered trees, creating a stark contrast between the whiteness of the snow and the dark clothes of the man.\\nThe atmosphere is calm and peaceful, with a soft blue light illuminating the scene, suggesting that it might be early morning or late evening. The sound of crunching snow beneath the man\'s feet can be heard as he makes", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 16, "num_frames": 66, "enhance_end": 1, "enhance_start": 0, "force_offload": true, "lora_strength": 1, "enhance_double": true, "enhance_single": true, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-24T00:10:21.698710Z", "created_at": "2025-01-24T00:03:00.696000Z", "data_removed": false, "error": null, "id": "w7j2vac1v1rm80cmjpf8kpdzaw", "input": { "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a serene and picturesque snow-covered landscape. The scene is set in a hilly area with dense snow covering the ground, trees, and rocks. A man dressed in a dark coat and hat is walking along a snowy path, carrying a briefcase. The path is surrounded by large boulders and snow-covered trees, creating a stark contrast between the whiteness of the snow and the dark clothes of the man.\nThe atmosphere is calm and peaceful, with a soft blue light illuminating the scene, suggesting that it might be early morning or late evening. The sound of crunching snow beneath the man's feet can be heard as he makes", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 16, "num_frames": 66, "enhance_end": 1, "enhance_start": 0, "force_offload": true, "lora_strength": 1, "enhance_double": true, "enhance_single": true, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 }, "logs": "Seed set to: 12345\n⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements\n⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements\nChecking inputs\n====================================\nChecking weights\n✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae\n✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models\n====================================\nRunning workflow\n[ComfyUI] got prompt\nExecuting node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode\n[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 147\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77\n[ComfyUI] Input (height, width, video_length) = (368, 640, 65)\n[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps\n[ComfyUI]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:53, 2.31s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:37, 2.03s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:41, 2.16s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:42, 2.22s/it]\n[ComfyUI] 10%|█ | 5/50 [00:11<01:41, 2.25s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.27s/it]\n[ComfyUI] 14%|█▍ | 7/50 [00:15<01:38, 2.28s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:36, 2.29s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.29s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.30s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.30s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.30s/it]\n[ComfyUI] 26%|██▌ | 13/50 [00:29<01:25, 2.30s/it]\n[ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.30s/it]\n[ComfyUI] 30%|███ | 15/50 [00:34<01:20, 2.30s/it]\n[ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it]\n[ComfyUI] 34%|███▍ | 17/50 [00:38<01:16, 2.31s/it]\n[ComfyUI] 36%|███▌ | 18/50 [00:41<01:13, 2.30s/it]\n[ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it]\n[ComfyUI] 40%|████ | 20/50 [00:45<01:09, 2.30s/it]\n[ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it]\n[ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it]\n[ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it]\n[ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it]\n[ComfyUI] 50%|█████ | 25/50 [00:57<00:57, 2.30s/it]\n[ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it]\n[ComfyUI] 54%|█████▍ | 27/50 [01:01<00:53, 2.30s/it]\n[ComfyUI] 56%|█████▌ | 28/50 [01:04<00:50, 2.30s/it]\n[ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it]\n[ComfyUI] 60%|██████ | 30/50 [01:08<00:46, 2.30s/it]\n[ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.30s/it]\n[ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it]\n[ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it]\n[ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it]\n[ComfyUI] 70%|███████ | 35/50 [01:20<00:34, 2.30s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:27<00:27, 2.30s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/it]\n[ComfyUI] 80%|████████ | 40/50 [01:31<00:23, 2.30s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [01:34<00:20, 2.30s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.30s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it]\n[ComfyUI] 90%|█████████ | 45/50 [01:43<00:11, 2.30s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:50<00:04, 2.30s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it]\n[ComfyUI] Allocated memory: memory=12.300 GB\n[ComfyUI] Max allocated memory: max_memory=15.099 GB\n[ComfyUI] Max reserved memory: max_reserved=16.344 GB\nExecuting node 5, title: HunyuanVideo Decode, class type: HyVideoDecode\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.48s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.25s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.29s/it]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.45it/s]\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.52it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.99it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.90it/s]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\nExecuting node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 64.37it/s]\n[ComfyUI] Prompt executed in 135.29 seconds\noutputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}}\n====================================\nHunyuanVideo_00001.png\nHunyuanVideo_00001.mp4", "metrics": { "predict_time": 143.096934457, "total_time": 441.00271 }, "output": "https://replicate.delivery/xezq/386T4mjLrU5UP1O2ZscQAEhfsq7T7ClU6UXysTra3X02YEEKA/HunyuanVideo_00001.mp4", "started_at": "2025-01-24T00:07:58.601776Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-xjwylklf33avipxvvhocivg7gmjz6zi5sieuussp5ieihezhawqa", "get": "https://api.replicate.com/v1/predictions/w7j2vac1v1rm80cmjpf8kpdzaw", "cancel": "https://api.replicate.com/v1/predictions/w7j2vac1v1rm80cmjpf8kpdzaw/cancel" }, "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9" }Generated inSeed set to: 12345 ⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements ⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements Checking inputs ==================================== Checking weights ✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae ✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models ==================================== Running workflow [ComfyUI] got prompt Executing node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode [ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 147 [ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77 [ComfyUI] Input (height, width, video_length) = (368, 640, 65) [ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler [ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps [ComfyUI] [ComfyUI] 0%| | 0/50 [00:00<?, ?it/s] [ComfyUI] 2%|▏ | 1/50 [00:02<01:53, 2.31s/it] [ComfyUI] 4%|▍ | 2/50 [00:04<01:37, 2.03s/it] [ComfyUI] 6%|▌ | 3/50 [00:06<01:41, 2.16s/it] [ComfyUI] 8%|▊ | 4/50 [00:08<01:42, 2.22s/it] [ComfyUI] 10%|█ | 5/50 [00:11<01:41, 2.25s/it] [ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.27s/it] [ComfyUI] 14%|█▍ | 7/50 [00:15<01:38, 2.28s/it] [ComfyUI] 16%|█▌ | 8/50 [00:17<01:36, 2.29s/it] [ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.29s/it] [ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.30s/it] [ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.30s/it] [ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.30s/it] [ComfyUI] 26%|██▌ | 13/50 [00:29<01:25, 2.30s/it] [ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.30s/it] [ComfyUI] 30%|███ | 15/50 [00:34<01:20, 2.30s/it] [ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it] [ComfyUI] 34%|███▍ | 17/50 [00:38<01:16, 2.31s/it] [ComfyUI] 36%|███▌ | 18/50 [00:41<01:13, 2.30s/it] [ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it] [ComfyUI] 40%|████ | 20/50 [00:45<01:09, 2.30s/it] [ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it] [ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it] [ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it] [ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it] [ComfyUI] 50%|█████ | 25/50 [00:57<00:57, 2.30s/it] [ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it] [ComfyUI] 54%|█████▍ | 27/50 [01:01<00:53, 2.30s/it] [ComfyUI] 56%|█████▌ | 28/50 [01:04<00:50, 2.30s/it] [ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it] [ComfyUI] 60%|██████ | 30/50 [01:08<00:46, 2.30s/it] [ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.30s/it] [ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it] [ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it] [ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it] [ComfyUI] 70%|███████ | 35/50 [01:20<00:34, 2.30s/it] [ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it] [ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it] [ComfyUI] 76%|███████▌ | 38/50 [01:27<00:27, 2.30s/it] [ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/it] [ComfyUI] 80%|████████ | 40/50 [01:31<00:23, 2.30s/it] [ComfyUI] 82%|████████▏ | 41/50 [01:34<00:20, 2.30s/it] [ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.30s/it] [ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it] [ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it] [ComfyUI] 90%|█████████ | 45/50 [01:43<00:11, 2.30s/it] [ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it] [ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it] [ComfyUI] 96%|█████████▌| 48/50 [01:50<00:04, 2.30s/it] [ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it] [ComfyUI] Allocated memory: memory=12.300 GB [ComfyUI] Max allocated memory: max_memory=15.099 GB [ComfyUI] Max reserved memory: max_reserved=16.344 GB Executing node 5, title: HunyuanVideo Decode, class type: HyVideoDecode [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.48s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.25s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.29s/it] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.45it/s] [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.52it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.99it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.90it/s] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 64.37it/s] [ComfyUI] Prompt executed in 135.29 seconds outputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}} ==================================== HunyuanVideo_00001.png HunyuanVideo_00001.mp4Prediction
deepfates/hunyuan-the-matrix-trilogy:e84c3dd2IDc7tztjtthsrme0cmjr69p3ja4mStatusSucceededSourceAPIHardwareH100Total durationCreatedInput
- crf
- 19
- seed
- 12345
- steps
- 50
- width
- 640
- height
- 480
- prompt
- A video of THMTR, a wizard in a blue-gray robe, his face shadowed inside a hood, reads a book in a cyberpunk hacker's room with computers all over the place. He suddenly looks up and directly at the camera with glowing blue eyes. The lights flicker in a glitchy fashion as magic is being cast.
- lora_url
- scheduler
- DPMSolverMultistepScheduler
- flow_shift
- 9
- frame_rate
- 24
- num_frames
- 49
- enhance_end
- 1
- enhance_start
- 0
- force_offload
- lora_strength
- 1
- enhance_double
- enhance_single
- enhance_weight
- 0.3
- guidance_scale
- 6
- denoise_strength
- 1
{ "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 480, "prompt": "A video of THMTR, a wizard in a blue-gray robe, his face shadowed inside a hood, reads a book in a cyberpunk hacker's room with computers all over the place. He suddenly looks up and directly at the camera with glowing blue eyes. The lights flicker in a glitchy fashion as magic is being cast.", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 24, "num_frames": 49, "enhance_end": 1, "enhance_start": 0, "force_offload": true, "lora_strength": 1, "enhance_double": true, "enhance_single": true, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", { input: { crf: 19, seed: 12345, steps: 50, width: 640, height: 480, prompt: "A video of THMTR, a wizard in a blue-gray robe, his face shadowed inside a hood, reads a book in a cyberpunk hacker's room with computers all over the place. He suddenly looks up and directly at the camera with glowing blue eyes. The lights flicker in a glitchy fashion as magic is being cast.", lora_url: "", scheduler: "DPMSolverMultistepScheduler", flow_shift: 9, frame_rate: 24, num_frames: 49, enhance_end: 1, enhance_start: 0, force_offload: true, lora_strength: 1, enhance_double: true, enhance_single: true, enhance_weight: 0.3, guidance_scale: 6, denoise_strength: 1 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", input={ "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 480, "prompt": "A video of THMTR, a wizard in a blue-gray robe, his face shadowed inside a hood, reads a book in a cyberpunk hacker's room with computers all over the place. He suddenly looks up and directly at the camera with glowing blue eyes. The lights flicker in a glitchy fashion as magic is being cast.", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 24, "num_frames": 49, "enhance_end": 1, "enhance_start": 0, "force_offload": True, "lora_strength": 1, "enhance_double": True, "enhance_single": True, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", "input": { "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 480, "prompt": "A video of THMTR, a wizard in a blue-gray robe, his face shadowed inside a hood, reads a book in a cyberpunk hacker\'s room with computers all over the place. He suddenly looks up and directly at the camera with glowing blue eyes. The lights flicker in a glitchy fashion as magic is being cast.", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 24, "num_frames": 49, "enhance_end": 1, "enhance_start": 0, "force_offload": true, "lora_strength": 1, "enhance_double": true, "enhance_single": true, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-24T02:25:26.905632Z", "created_at": "2025-01-24T02:02:59.598000Z", "data_removed": false, "error": null, "id": "c7tztjtthsrme0cmjr69p3ja4m", "input": { "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 480, "prompt": "A video of THMTR, a wizard in a blue-gray robe, his face shadowed inside a hood, reads a book in a cyberpunk hacker's room with computers all over the place. He suddenly looks up and directly at the camera with glowing blue eyes. The lights flicker in a glitchy fashion as magic is being cast.", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 24, "num_frames": 49, "enhance_end": 1, "enhance_start": 0, "force_offload": true, "lora_strength": 1, "enhance_double": true, "enhance_single": true, "enhance_weight": 0.3, "guidance_scale": 6, "denoise_strength": 1 }, "logs": "Seed set to: 12345\nChecking inputs\n====================================\nChecking weights\n✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models\n✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae\n====================================\nRunning workflow\n[ComfyUI] got prompt\n[ComfyUI] Input (height, width, video_length) = (480, 640, 49)\n[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] Sampling 49 frames in 13 latents at 640x480 with 50 inference steps\n[ComfyUI]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:52, 2.30s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.02s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.14s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.20s/it]\n[ComfyUI] 10%|█ | 5/50 [00:11<01:40, 2.24s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.26s/it]\n[ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.27s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.28s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.28s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.29s/it]\n[ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.29s/it]\n[ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.30s/it]\n[ComfyUI] 30%|███ | 15/50 [00:33<01:20, 2.30s/it]\n[ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it]\n[ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.30s/it]\n[ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.30s/it]\n[ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it]\n[ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.30s/it]\n[ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it]\n[ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it]\n[ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it]\n[ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it]\n[ComfyUI] 50%|█████ | 25/50 [00:56<00:57, 2.30s/it]\n[ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it]\n[ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.30s/it]\n[ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.30s/it]\n[ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it]\n[ComfyUI] 60%|██████ | 30/50 [01:08<00:45, 2.30s/it]\n[ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.30s/it]\n[ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it]\n[ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it]\n[ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it]\n[ComfyUI] 70%|███████ | 35/50 [01:19<00:34, 2.30s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.30s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/it]\n[ComfyUI] 80%|████████ | 40/50 [01:31<00:22, 2.30s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.30s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.30s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it]\n[ComfyUI] 90%|█████████ | 45/50 [01:42<00:11, 2.30s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.30s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it]\n[ComfyUI] Allocated memory: memory=12.300 GB\n[ComfyUI] Max allocated memory: max_memory=15.089 GB\n[ComfyUI] Max reserved memory: max_reserved=16.312 GB\nExecuting node 5, title: HunyuanVideo Decode, class type: HyVideoDecode\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/3 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 33%|███▎ | 1/3 [00:01<00:02, 1.11s/it]\n[ComfyUI] Decoding rows: 67%|██████▋ | 2/3 [00:02<00:01, 1.14s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 3/3 [00:02<00:00, 1.19it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 3/3 [00:02<00:00, 1.09it/s]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/3 [00:00<?, ?it/s]\nExecuting node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine\n[ComfyUI] Blending tiles: 100%|██████████| 3/3 [00:00<00:00, 65.65it/s]\n[ComfyUI] Prompt executed in 125.62 seconds\noutputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 24.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}}\n====================================\nHunyuanVideo_00001.png\nHunyuanVideo_00001.mp4", "metrics": { "predict_time": 135.127949614, "total_time": 1347.307632 }, "output": "https://replicate.delivery/xezq/ynYY8XTLzyKUIBQ0uIILRD8bcgrulJgLWhx9Uyy2vItFsCCF/HunyuanVideo_00001.mp4", "started_at": "2025-01-24T02:23:11.777682Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-3gwc2hnxre2q6dsg3spry3yf5o3egalgqmmsf5osxdpqlrx7llra", "get": "https://api.replicate.com/v1/predictions/c7tztjtthsrme0cmjr69p3ja4m", "cancel": "https://api.replicate.com/v1/predictions/c7tztjtthsrme0cmjr69p3ja4m/cancel" }, "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9" }Generated inSeed set to: 12345 Checking inputs ==================================== Checking weights ✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models ✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae ==================================== Running workflow [ComfyUI] got prompt [ComfyUI] Input (height, width, video_length) = (480, 640, 49) [ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler [ComfyUI] Sampling 49 frames in 13 latents at 640x480 with 50 inference steps [ComfyUI] [ComfyUI] 0%| | 0/50 [00:00<?, ?it/s] [ComfyUI] 2%|▏ | 1/50 [00:02<01:52, 2.30s/it] [ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.02s/it] [ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.14s/it] [ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.20s/it] [ComfyUI] 10%|█ | 5/50 [00:11<01:40, 2.24s/it] [ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.26s/it] [ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.27s/it] [ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.28s/it] [ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.28s/it] [ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it] [ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it] [ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.29s/it] [ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.29s/it] [ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.30s/it] [ComfyUI] 30%|███ | 15/50 [00:33<01:20, 2.30s/it] [ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it] [ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.30s/it] [ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.30s/it] [ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it] [ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.30s/it] [ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it] [ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it] [ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it] [ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it] [ComfyUI] 50%|█████ | 25/50 [00:56<00:57, 2.30s/it] [ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it] [ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.30s/it] [ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.30s/it] [ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it] [ComfyUI] 60%|██████ | 30/50 [01:08<00:45, 2.30s/it] [ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.30s/it] [ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it] [ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it] [ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it] [ComfyUI] 70%|███████ | 35/50 [01:19<00:34, 2.30s/it] [ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it] [ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it] [ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.30s/it] [ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/it] [ComfyUI] 80%|████████ | 40/50 [01:31<00:22, 2.30s/it] [ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.30s/it] [ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.30s/it] [ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it] [ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it] [ComfyUI] 90%|█████████ | 45/50 [01:42<00:11, 2.30s/it] [ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it] [ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it] [ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.30s/it] [ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it] [ComfyUI] Allocated memory: memory=12.300 GB [ComfyUI] Max allocated memory: max_memory=15.089 GB [ComfyUI] Max reserved memory: max_reserved=16.312 GB Executing node 5, title: HunyuanVideo Decode, class type: HyVideoDecode [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/3 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 33%|███▎ | 1/3 [00:01<00:02, 1.11s/it] [ComfyUI] Decoding rows: 67%|██████▋ | 2/3 [00:02<00:01, 1.14s/it] [ComfyUI] Decoding rows: 100%|██████████| 3/3 [00:02<00:00, 1.19it/s] [ComfyUI] Decoding rows: 100%|██████████| 3/3 [00:02<00:00, 1.09it/s] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/3 [00:00<?, ?it/s] Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine [ComfyUI] Blending tiles: 100%|██████████| 3/3 [00:00<00:00, 65.65it/s] [ComfyUI] Prompt executed in 125.62 seconds outputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 24.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}} ==================================== HunyuanVideo_00001.png HunyuanVideo_00001.mp4Prediction
deepfates/hunyuan-the-matrix-trilogy:e84c3dd2IDh01kexk0asrm80cmjs3v3cc0e0StatusSucceededSourceAPIHardwareH100Total durationCreatedInput
- seed
- 12345
- steps
- 50
- width
- 640
- height
- 360
- prompt
- A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace. In the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting. In the distance
- frame_rate
- 16
- num_frames
- 66
- lora_strength
- 1
- guidance_scale
- 6
{ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace.\nIn the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting.\nIn the distance", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", { input: { seed: 12345, steps: 50, width: 640, height: 360, prompt: "A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace.\nIn the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting.\nIn the distance", frame_rate: 16, num_frames: 66, lora_strength: 1, guidance_scale: 6 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", input={ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace.\nIn the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting.\nIn the distance", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace.\\nIn the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting.\\nIn the distance", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-24T03:20:26.509237Z", "created_at": "2025-01-24T03:07:27.702000Z", "data_removed": false, "error": null, "id": "h01kexk0asrm80cmjs3v3cc0e0", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace.\nIn the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting.\nIn the distance", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 }, "logs": "Seed set to: 12345\n⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements\n⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements\nChecking inputs\n====================================\nChecking weights\n✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models\n✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae\n====================================\nRunning workflow\n[ComfyUI] got prompt\nExecuting node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode\n[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 146\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77\n[ComfyUI] Input (height, width, video_length) = (368, 640, 65)\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps\n[ComfyUI]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:53, 2.31s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:37, 2.02s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:41, 2.15s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.21s/it]\n[ComfyUI] 10%|█ | 5/50 [00:11<01:41, 2.25s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.27s/it]\n[ComfyUI] 14%|█▍ | 7/50 [00:15<01:38, 2.28s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:36, 2.29s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:34, 2.29s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.30s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.30s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.30s/it]\n[ComfyUI] 26%|██▌ | 13/50 [00:29<01:25, 2.30s/it]\n[ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.30s/it]\n[ComfyUI] 30%|███ | 15/50 [00:34<01:20, 2.30s/it]\n[ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it]\n[ComfyUI] 34%|███▍ | 17/50 [00:38<01:16, 2.30s/it]\n[ComfyUI] 36%|███▌ | 18/50 [00:41<01:13, 2.30s/it]\n[ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.31s/it]\n[ComfyUI] 40%|████ | 20/50 [00:45<01:09, 2.31s/it]\n[ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.31s/it]\n[ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.31s/it]\n[ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.31s/it]\n[ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.31s/it]\n[ComfyUI] 50%|█████ | 25/50 [00:57<00:57, 2.31s/it]\n[ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.31s/it]\n[ComfyUI] 54%|█████▍ | 27/50 [01:01<00:53, 2.31s/it]\n[ComfyUI] 56%|█████▌ | 28/50 [01:04<00:50, 2.31s/it]\n[ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.31s/it]\n[ComfyUI] 60%|██████ | 30/50 [01:08<00:46, 2.31s/it]\n[ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.31s/it]\n[ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.31s/it]\n[ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.31s/it]\n[ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.31s/it]\n[ComfyUI] 70%|███████ | 35/50 [01:20<00:34, 2.31s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.31s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.31s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:27<00:27, 2.31s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.31s/it]\n[ComfyUI] 80%|████████ | 40/50 [01:31<00:23, 2.31s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [01:34<00:20, 2.31s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.31s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.31s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.31s/it]\n[ComfyUI] 90%|█████████ | 45/50 [01:43<00:11, 2.31s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.31s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.31s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:50<00:04, 2.31s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.31s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.31s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it]\n[ComfyUI] Allocated memory: memory=12.300 GB\n[ComfyUI] Max allocated memory: max_memory=15.099 GB\n[ComfyUI] Max reserved memory: max_reserved=16.281 GB\nExecuting node 5, title: HunyuanVideo Decode, class type: HyVideoDecode\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.74s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.36s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.42s/it]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.54it/s]\n[ComfyUI] \n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.51it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.99it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.91it/s]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\nExecuting node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 64.15it/s]\n[ComfyUI] Prompt executed in 135.73 seconds\noutputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}}\n====================================\nHunyuanVideo_00001.png\nHunyuanVideo_00001.mp4", "metrics": { "predict_time": 137.416584363, "total_time": 778.807237 }, "output": "https://replicate.delivery/xezq/qDLd6D6zyeXLCCAtK9hNeblN3ZF8C2og7NiBLmpeVemqPugQB/HunyuanVideo_00001.mp4", "started_at": "2025-01-24T03:18:09.092652Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-jnrsh3yvtuwstvhxj3leseuu3mf64k753kfdjgiuar4hkb73hpna", "get": "https://api.replicate.com/v1/predictions/h01kexk0asrm80cmjs3v3cc0e0", "cancel": "https://api.replicate.com/v1/predictions/h01kexk0asrm80cmjs3v3cc0e0/cancel" }, "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9" }Generated inSeed set to: 12345 ⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements ⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements Checking inputs ==================================== Checking weights ✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models ✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae ==================================== Running workflow [ComfyUI] got prompt Executing node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode [ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 146 [ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77 [ComfyUI] Input (height, width, video_length) = (368, 640, 65) Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler [ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps [ComfyUI] [ComfyUI] 0%| | 0/50 [00:00<?, ?it/s] [ComfyUI] 2%|▏ | 1/50 [00:02<01:53, 2.31s/it] [ComfyUI] 4%|▍ | 2/50 [00:04<01:37, 2.02s/it] [ComfyUI] 6%|▌ | 3/50 [00:06<01:41, 2.15s/it] [ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.21s/it] [ComfyUI] 10%|█ | 5/50 [00:11<01:41, 2.25s/it] [ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.27s/it] [ComfyUI] 14%|█▍ | 7/50 [00:15<01:38, 2.28s/it] [ComfyUI] 16%|█▌ | 8/50 [00:17<01:36, 2.29s/it] [ComfyUI] 18%|█▊ | 9/50 [00:20<01:34, 2.29s/it] [ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.30s/it] [ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.30s/it] [ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.30s/it] [ComfyUI] 26%|██▌ | 13/50 [00:29<01:25, 2.30s/it] [ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.30s/it] [ComfyUI] 30%|███ | 15/50 [00:34<01:20, 2.30s/it] [ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it] [ComfyUI] 34%|███▍ | 17/50 [00:38<01:16, 2.30s/it] [ComfyUI] 36%|███▌ | 18/50 [00:41<01:13, 2.30s/it] [ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.31s/it] [ComfyUI] 40%|████ | 20/50 [00:45<01:09, 2.31s/it] [ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.31s/it] [ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.31s/it] [ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.31s/it] [ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.31s/it] [ComfyUI] 50%|█████ | 25/50 [00:57<00:57, 2.31s/it] [ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.31s/it] [ComfyUI] 54%|█████▍ | 27/50 [01:01<00:53, 2.31s/it] [ComfyUI] 56%|█████▌ | 28/50 [01:04<00:50, 2.31s/it] [ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.31s/it] [ComfyUI] 60%|██████ | 30/50 [01:08<00:46, 2.31s/it] [ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.31s/it] [ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.31s/it] [ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.31s/it] [ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.31s/it] [ComfyUI] 70%|███████ | 35/50 [01:20<00:34, 2.31s/it] [ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.31s/it] [ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.31s/it] [ComfyUI] 76%|███████▌ | 38/50 [01:27<00:27, 2.31s/it] [ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.31s/it] [ComfyUI] 80%|████████ | 40/50 [01:31<00:23, 2.31s/it] [ComfyUI] 82%|████████▏ | 41/50 [01:34<00:20, 2.31s/it] [ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.31s/it] [ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.31s/it] [ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.31s/it] [ComfyUI] 90%|█████████ | 45/50 [01:43<00:11, 2.31s/it] [ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.31s/it] [ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.31s/it] [ComfyUI] 96%|█████████▌| 48/50 [01:50<00:04, 2.31s/it] [ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.31s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.31s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it] [ComfyUI] Allocated memory: memory=12.300 GB [ComfyUI] Max allocated memory: max_memory=15.099 GB [ComfyUI] Max reserved memory: max_reserved=16.281 GB Executing node 5, title: HunyuanVideo Decode, class type: HyVideoDecode [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.74s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.36s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.42s/it] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.54it/s] [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.51it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.99it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.91it/s] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 64.15it/s] [ComfyUI] Prompt executed in 135.73 seconds outputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}} ==================================== HunyuanVideo_00001.png HunyuanVideo_00001.mp4Prediction
deepfates/hunyuan-the-matrix-trilogy:e84c3dd2ID56dbaezyenrme0cmk5wrpztzhwStatusSucceededSourceAPIHardwareH100Total durationCreatedInput
- seed
- 12345
- steps
- 50
- width
- 640
- height
- 360
- prompt
- A video in the style of THMTR, THMTR The video clip depicts a high-speed chase scene set in a desert environment. The primary focus is on a vehicle, which appears to be a modified off-road truck, speeding across the sandy terrain. The truck is kicking up a large cloud of sand and dust, indicating its high speed and the rough terrain it is traversing. The vehicle is equipped with a large, mounted weapon system on its back, suggesting it is part of a military or law enforcement operation. The background features a vast desert landscape with sand dunes stretching into the distance. The sky is clear with a few scattered clouds, and the overall lighting suggests it is daytime. The
- frame_rate
- 16
- num_frames
- 66
- lora_strength
- 1
- guidance_scale
- 6
{ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a high-speed chase scene set in a desert environment. The primary focus is on a vehicle, which appears to be a modified off-road truck, speeding across the sandy terrain. The truck is kicking up a large cloud of sand and dust, indicating its high speed and the rough terrain it is traversing. The vehicle is equipped with a large, mounted weapon system on its back, suggesting it is part of a military or law enforcement operation.\nThe background features a vast desert landscape with sand dunes stretching into the distance. The sky is clear with a few scattered clouds, and the overall lighting suggests it is daytime. The", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", { input: { seed: 12345, steps: 50, width: 640, height: 360, prompt: "A video in the style of THMTR, THMTR The video clip depicts a high-speed chase scene set in a desert environment. The primary focus is on a vehicle, which appears to be a modified off-road truck, speeding across the sandy terrain. The truck is kicking up a large cloud of sand and dust, indicating its high speed and the rough terrain it is traversing. The vehicle is equipped with a large, mounted weapon system on its back, suggesting it is part of a military or law enforcement operation.\nThe background features a vast desert landscape with sand dunes stretching into the distance. The sky is clear with a few scattered clouds, and the overall lighting suggests it is daytime. The", frame_rate: 16, num_frames: 66, lora_strength: 1, guidance_scale: 6 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", input={ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a high-speed chase scene set in a desert environment. The primary focus is on a vehicle, which appears to be a modified off-road truck, speeding across the sandy terrain. The truck is kicking up a large cloud of sand and dust, indicating its high speed and the rough terrain it is traversing. The vehicle is equipped with a large, mounted weapon system on its back, suggesting it is part of a military or law enforcement operation.\nThe background features a vast desert landscape with sand dunes stretching into the distance. The sky is clear with a few scattered clouds, and the overall lighting suggests it is daytime. The", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a high-speed chase scene set in a desert environment. The primary focus is on a vehicle, which appears to be a modified off-road truck, speeding across the sandy terrain. The truck is kicking up a large cloud of sand and dust, indicating its high speed and the rough terrain it is traversing. The vehicle is equipped with a large, mounted weapon system on its back, suggesting it is part of a military or law enforcement operation.\\nThe background features a vast desert landscape with sand dunes stretching into the distance. The sky is clear with a few scattered clouds, and the overall lighting suggests it is daytime. The", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-24T18:10:13.348331Z", "created_at": "2025-01-24T18:01:36.629000Z", "data_removed": false, "error": null, "id": "56dbaezyenrme0cmk5wrpztzhw", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts a high-speed chase scene set in a desert environment. The primary focus is on a vehicle, which appears to be a modified off-road truck, speeding across the sandy terrain. The truck is kicking up a large cloud of sand and dust, indicating its high speed and the rough terrain it is traversing. The vehicle is equipped with a large, mounted weapon system on its back, suggesting it is part of a military or law enforcement operation.\nThe background features a vast desert landscape with sand dunes stretching into the distance. The sky is clear with a few scattered clouds, and the overall lighting suggests it is daytime. The", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 }, "logs": "Seed set to: 12345\n⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements\n⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements\n�� USING REPLICATE WEIGHTS (preferred method)\n🎯 USING REPLICATE WEIGHTS TAR FILE 🎯\n----------------------------------------\n📦 Processing replicate weights tar file...\n🔄 Will rename LoRA to: replicate_9ab42fb9-f886-4086-bcd2-78b1903eacd6.safetensors\n📂 Extracting tar contents...\n✅ Found lora_comfyui.safetensors in tar\n✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_9ab42fb9-f886-4086-bcd2-78b1903eacd6.safetensors\n----------------------------------------\nChecking inputs\n====================================\nChecking weights\n✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae\n✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models\n====================================\nRunning workflow\n[ComfyUI] got prompt\nExecuting node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode\n[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 142\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77\nExecuting node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect\nExecuting node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader\n[ComfyUI] model_type FLOW\n[ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Using accelerate to load and assign model weights to device...\n[ComfyUI] Loading LoRA: replicate_9ab42fb9-f886-4086-bcd2-78b1903eacd6 with strength: 1.0\n[ComfyUI] Requested to load HyVideoModel\n[ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True\n[ComfyUI] Input (height, width, video_length) = (368, 640, 65)\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps\n[ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['n_tokens', 'num_train_timesteps'])])\n[ComfyUI]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:52, 2.30s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.02s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.14s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.20s/it]\n[ComfyUI] 10%|█ | 5/50 [00:11<01:40, 2.24s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.26s/it]\n[ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.27s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.28s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.28s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.29s/it]\n[ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.29s/it]\n[ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.29s/it]\n[ComfyUI] 30%|███ | 15/50 [00:33<01:20, 2.30s/it]\n[ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it]\n[ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.30s/it]\n[ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.30s/it]\n[ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it]\n[ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.30s/it]\n[ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it]\n[ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it]\n[ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it]\n[ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it]\n[ComfyUI] 50%|█████ | 25/50 [00:56<00:57, 2.30s/it]\n[ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it]\n[ComfyUI] 54%|█████▍ | 27/50 [01:01<00:53, 2.31s/it]\n[ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.31s/it]\n[ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it]\n[ComfyUI] 60%|██████ | 30/50 [01:08<00:46, 2.30s/it]\n[ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.30s/it]\n[ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it]\n[ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it]\n[ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it]\n[ComfyUI] 70%|███████ | 35/50 [01:19<00:34, 2.30s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.30s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/it]\n[ComfyUI] 80%|████████ | 40/50 [01:31<00:22, 2.30s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.30s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.30s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it]\n[ComfyUI] 90%|█████████ | 45/50 [01:42<00:11, 2.30s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.30s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it]\n[ComfyUI] Allocated memory: memory=12.300 GB\n[ComfyUI] Max allocated memory: max_memory=15.099 GB\n[ComfyUI] Max reserved memory: max_reserved=16.281 GB\nExecuting node 5, title: HunyuanVideo Decode, class type: HyVideoDecode\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.46s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.24s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.27s/it]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.98it/s]\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.56it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.03it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.95it/s]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\nExecuting node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 63.98it/s]\n[ComfyUI] Prompt executed in 142.58 seconds\noutputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}}\n====================================\nHunyuanVideo_00001.png\nHunyuanVideo_00001.mp4", "metrics": { "predict_time": 156.098697151, "total_time": 516.719331 }, "output": "https://replicate.delivery/xezq/2Oll93ewgYSzQiy6WHByCBwDlf1g4eDGF8rhK6Si8ZTLMxQoA/HunyuanVideo_00001.mp4", "started_at": "2025-01-24T18:07:37.249634Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-57hp2c543n2gvt7uhsx7ssp22nliryeb7pzysh7cygjf6aea3i6q", "get": "https://api.replicate.com/v1/predictions/56dbaezyenrme0cmk5wrpztzhw", "cancel": "https://api.replicate.com/v1/predictions/56dbaezyenrme0cmk5wrpztzhw/cancel" }, "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9" }Generated inSeed set to: 12345 ⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements ⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements �� USING REPLICATE WEIGHTS (preferred method) 🎯 USING REPLICATE WEIGHTS TAR FILE 🎯 ---------------------------------------- 📦 Processing replicate weights tar file... 🔄 Will rename LoRA to: replicate_9ab42fb9-f886-4086-bcd2-78b1903eacd6.safetensors 📂 Extracting tar contents... ✅ Found lora_comfyui.safetensors in tar ✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_9ab42fb9-f886-4086-bcd2-78b1903eacd6.safetensors ---------------------------------------- Checking inputs ==================================== Checking weights ✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae ✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models ==================================== Running workflow [ComfyUI] got prompt Executing node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode [ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 142 [ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77 Executing node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect Executing node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader [ComfyUI] model_type FLOW [ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Using accelerate to load and assign model weights to device... [ComfyUI] Loading LoRA: replicate_9ab42fb9-f886-4086-bcd2-78b1903eacd6 with strength: 1.0 [ComfyUI] Requested to load HyVideoModel [ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True [ComfyUI] Input (height, width, video_length) = (368, 640, 65) Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler [ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps [ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['n_tokens', 'num_train_timesteps'])]) [ComfyUI] [ComfyUI] 0%| | 0/50 [00:00<?, ?it/s] [ComfyUI] 2%|▏ | 1/50 [00:02<01:52, 2.30s/it] [ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.02s/it] [ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.14s/it] [ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.20s/it] [ComfyUI] 10%|█ | 5/50 [00:11<01:40, 2.24s/it] [ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.26s/it] [ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.27s/it] [ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.28s/it] [ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.28s/it] [ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it] [ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it] [ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.29s/it] [ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.29s/it] [ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.29s/it] [ComfyUI] 30%|███ | 15/50 [00:33<01:20, 2.30s/it] [ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it] [ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.30s/it] [ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.30s/it] [ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it] [ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.30s/it] [ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it] [ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it] [ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it] [ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it] [ComfyUI] 50%|█████ | 25/50 [00:56<00:57, 2.30s/it] [ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it] [ComfyUI] 54%|█████▍ | 27/50 [01:01<00:53, 2.31s/it] [ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.31s/it] [ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it] [ComfyUI] 60%|██████ | 30/50 [01:08<00:46, 2.30s/it] [ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.30s/it] [ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it] [ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it] [ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it] [ComfyUI] 70%|███████ | 35/50 [01:19<00:34, 2.30s/it] [ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it] [ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it] [ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.30s/it] [ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/it] [ComfyUI] 80%|████████ | 40/50 [01:31<00:22, 2.30s/it] [ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.30s/it] [ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.30s/it] [ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it] [ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it] [ComfyUI] 90%|█████████ | 45/50 [01:42<00:11, 2.30s/it] [ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it] [ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it] [ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.30s/it] [ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it] [ComfyUI] Allocated memory: memory=12.300 GB [ComfyUI] Max allocated memory: max_memory=15.099 GB [ComfyUI] Max reserved memory: max_reserved=16.281 GB Executing node 5, title: HunyuanVideo Decode, class type: HyVideoDecode [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.46s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.24s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.27s/it] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.98it/s] [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.56it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.03it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.95it/s] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 63.98it/s] [ComfyUI] Prompt executed in 142.58 seconds outputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}} ==================================== HunyuanVideo_00001.png HunyuanVideo_00001.mp4Prediction
deepfates/hunyuan-the-matrix-trilogy:e84c3dd2IDng0bb86fenrm80cmk5x9pfkfrgStatusSucceededSourceAPIHardwareH100Total durationCreatedInput
- seed
- 12345
- steps
- 50
- width
- 640
- height
- 360
- prompt
- A video in the style of THMTR, THMTR The video clip features three individuals standing in a red elevator. The person on the left is wearing a purple uniform with gold buttons and a matching cap, standing with one hand on the elevator door. The person in the center is seated in a chair, wearing a light blue suit with a white shirt and a black bow tie. This individual has a mustache and is looking directly at the camera. The person on the right is also wearing a purple uniform with a cap that has the word BOBBY written on it. The background of the elevator is a vibrant red, creating a striking contrast with the purple uniforms. The overall scene
- frame_rate
- 16
- num_frames
- 66
- lora_strength
- 1
- guidance_scale
- 6
{ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip features three individuals standing in a red elevator. The person on the left is wearing a purple uniform with gold buttons and a matching cap, standing with one hand on the elevator door. The person in the center is seated in a chair, wearing a light blue suit with a white shirt and a black bow tie. This individual has a mustache and is looking directly at the camera. The person on the right is also wearing a purple uniform with a cap that has the word BOBBY written on it. The background of the elevator is a vibrant red, creating a striking contrast with the purple uniforms. The overall scene", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", { input: { seed: 12345, steps: 50, width: 640, height: 360, prompt: "A video in the style of THMTR, THMTR The video clip features three individuals standing in a red elevator. The person on the left is wearing a purple uniform with gold buttons and a matching cap, standing with one hand on the elevator door. The person in the center is seated in a chair, wearing a light blue suit with a white shirt and a black bow tie. This individual has a mustache and is looking directly at the camera. The person on the right is also wearing a purple uniform with a cap that has the word BOBBY written on it. The background of the elevator is a vibrant red, creating a striking contrast with the purple uniforms. The overall scene", frame_rate: 16, num_frames: 66, lora_strength: 1, guidance_scale: 6 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", input={ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip features three individuals standing in a red elevator. The person on the left is wearing a purple uniform with gold buttons and a matching cap, standing with one hand on the elevator door. The person in the center is seated in a chair, wearing a light blue suit with a white shirt and a black bow tie. This individual has a mustache and is looking directly at the camera. The person on the right is also wearing a purple uniform with a cap that has the word BOBBY written on it. The background of the elevator is a vibrant red, creating a striking contrast with the purple uniforms. The overall scene", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip features three individuals standing in a red elevator. The person on the left is wearing a purple uniform with gold buttons and a matching cap, standing with one hand on the elevator door. The person in the center is seated in a chair, wearing a light blue suit with a white shirt and a black bow tie. This individual has a mustache and is looking directly at the camera. The person on the right is also wearing a purple uniform with a cap that has the word BOBBY written on it. The background of the elevator is a vibrant red, creating a striking contrast with the purple uniforms. The overall scene", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-24T18:15:18.811896Z", "created_at": "2025-01-24T18:02:30.133000Z", "data_removed": false, "error": null, "id": "ng0bb86fenrm80cmk5x9pfkfrg", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip features three individuals standing in a red elevator. The person on the left is wearing a purple uniform with gold buttons and a matching cap, standing with one hand on the elevator door. The person in the center is seated in a chair, wearing a light blue suit with a white shirt and a black bow tie. This individual has a mustache and is looking directly at the camera. The person on the right is also wearing a purple uniform with a cap that has the word BOBBY written on it. The background of the elevator is a vibrant red, creating a striking contrast with the purple uniforms. The overall scene", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 }, "logs": "Seed set to: 12345\n⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements\n⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements\n�� USING REPLICATE WEIGHTS (preferred method)\n🎯 USING REPLICATE WEIGHTS TAR FILE 🎯\n----------------------------------------\n📦 Processing replicate weights tar file...\n🔄 Will rename LoRA to: replicate_d5433b50-ceb8-437f-8a4f-0759331d9b70.safetensors\n📂 Extracting tar contents...\n✅ Found lora_comfyui.safetensors in tar\n✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_d5433b50-ceb8-437f-8a4f-0759331d9b70.safetensors\n----------------------------------------\nChecking inputs\n====================================\nChecking weights\n✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae\n✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models\n====================================\nRunning workflow\n[ComfyUI] got prompt\nExecuting node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode\n[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 140\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77\nExecuting node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect\nExecuting node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader\n[ComfyUI] model_type FLOW\n[ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Using accelerate to load and assign model weights to device...\n[ComfyUI] Loading LoRA: replicate_d5433b50-ceb8-437f-8a4f-0759331d9b70 with strength: 1.0\n[ComfyUI] Requested to load HyVideoModel\n[ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True\n[ComfyUI] Input (height, width, video_length) = (368, 640, 65)\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps\n[ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['n_tokens', 'num_train_timesteps'])])\n[ComfyUI]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:52, 2.30s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.02s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.14s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.20s/it]\n[ComfyUI] 10%|█ | 5/50 [00:11<01:40, 2.24s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.26s/it]\n[ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.27s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.28s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.28s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.29s/it]\n[ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.29s/it]\n[ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.29s/it]\n[ComfyUI] 30%|███ | 15/50 [00:33<01:20, 2.30s/it]\n[ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it]\n[ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.30s/it]\n[ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.30s/it]\n[ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it]\n[ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.30s/it]\n[ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it]\n[ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it]\n[ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it]\n[ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it]\n[ComfyUI] 50%|█████ | 25/50 [00:56<00:57, 2.30s/it]\n[ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it]\n[ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.30s/it]\n[ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.30s/it]\n[ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it]\n[ComfyUI] 60%|██████ | 30/50 [01:08<00:45, 2.30s/it]\n[ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.30s/it]\n[ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it]\n[ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it]\n[ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it]\n[ComfyUI] 70%|███████ | 35/50 [01:19<00:34, 2.30s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.30s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/it]\n[ComfyUI] 80%|████████ | 40/50 [01:31<00:22, 2.30s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.30s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [01:35<00:18, 2.30s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it]\n[ComfyUI] 90%|█████████ | 45/50 [01:42<00:11, 2.30s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.30s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it]\n[ComfyUI] Allocated memory: memory=12.300 GB\n[ComfyUI] Max allocated memory: max_memory=15.099 GB\n[ComfyUI] Max reserved memory: max_reserved=16.281 GB\nExecuting node 5, title: HunyuanVideo Decode, class type: HyVideoDecode\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.45s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.23s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.27s/it]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.88it/s]\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.56it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.04it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.95it/s]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\nExecuting node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 64.31it/s]\n[ComfyUI] Prompt executed in 142.24 seconds\noutputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}}\n====================================\nHunyuanVideo_00001.png\nHunyuanVideo_00001.mp4", "metrics": { "predict_time": 156.118323492, "total_time": 768.678896 }, "output": "https://replicate.delivery/xezq/8eVoBv1bVftlOkb6UVqQ2MBcDe7VGFtRyc1rdcYvzY8sVxQoA/HunyuanVideo_00001.mp4", "started_at": "2025-01-24T18:12:42.693572Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-ldqfp7pdyywid56vnkoqkebgnqfoi33jtcxakrjwhthcq3sgvetq", "get": "https://api.replicate.com/v1/predictions/ng0bb86fenrm80cmk5x9pfkfrg", "cancel": "https://api.replicate.com/v1/predictions/ng0bb86fenrm80cmk5x9pfkfrg/cancel" }, "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9" }Generated inSeed set to: 12345 ⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements ⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements �� USING REPLICATE WEIGHTS (preferred method) 🎯 USING REPLICATE WEIGHTS TAR FILE 🎯 ---------------------------------------- 📦 Processing replicate weights tar file... 🔄 Will rename LoRA to: replicate_d5433b50-ceb8-437f-8a4f-0759331d9b70.safetensors 📂 Extracting tar contents... ✅ Found lora_comfyui.safetensors in tar ✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_d5433b50-ceb8-437f-8a4f-0759331d9b70.safetensors ---------------------------------------- Checking inputs ==================================== Checking weights ✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae ✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models ==================================== Running workflow [ComfyUI] got prompt Executing node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode [ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 140 [ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77 Executing node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect Executing node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader [ComfyUI] model_type FLOW [ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Using accelerate to load and assign model weights to device... [ComfyUI] Loading LoRA: replicate_d5433b50-ceb8-437f-8a4f-0759331d9b70 with strength: 1.0 [ComfyUI] Requested to load HyVideoModel [ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True [ComfyUI] Input (height, width, video_length) = (368, 640, 65) Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler [ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps [ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['n_tokens', 'num_train_timesteps'])]) [ComfyUI] [ComfyUI] 0%| | 0/50 [00:00<?, ?it/s] [ComfyUI] 2%|▏ | 1/50 [00:02<01:52, 2.30s/it] [ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.02s/it] [ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.14s/it] [ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.20s/it] [ComfyUI] 10%|█ | 5/50 [00:11<01:40, 2.24s/it] [ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.26s/it] [ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.27s/it] [ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.28s/it] [ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.28s/it] [ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it] [ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it] [ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.29s/it] [ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.29s/it] [ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.29s/it] [ComfyUI] 30%|███ | 15/50 [00:33<01:20, 2.30s/it] [ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it] [ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.30s/it] [ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.30s/it] [ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it] [ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.30s/it] [ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it] [ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it] [ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it] [ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it] [ComfyUI] 50%|█████ | 25/50 [00:56<00:57, 2.30s/it] [ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it] [ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.30s/it] [ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.30s/it] [ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it] [ComfyUI] 60%|██████ | 30/50 [01:08<00:45, 2.30s/it] [ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.30s/it] [ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it] [ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it] [ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it] [ComfyUI] 70%|███████ | 35/50 [01:19<00:34, 2.30s/it] [ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it] [ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it] [ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.30s/it] [ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/it] [ComfyUI] 80%|████████ | 40/50 [01:31<00:22, 2.30s/it] [ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.30s/it] [ComfyUI] 84%|████████▍ | 42/50 [01:35<00:18, 2.30s/it] [ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it] [ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it] [ComfyUI] 90%|█████████ | 45/50 [01:42<00:11, 2.30s/it] [ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it] [ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it] [ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.30s/it] [ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it] [ComfyUI] Allocated memory: memory=12.300 GB [ComfyUI] Max allocated memory: max_memory=15.099 GB [ComfyUI] Max reserved memory: max_reserved=16.281 GB Executing node 5, title: HunyuanVideo Decode, class type: HyVideoDecode [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.45s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.23s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.27s/it] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.88it/s] [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.56it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.04it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.95it/s] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 64.31it/s] [ComfyUI] Prompt executed in 142.24 seconds outputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}} ==================================== HunyuanVideo_00001.png HunyuanVideo_00001.mp4Prediction
deepfates/hunyuan-the-matrix-trilogy:e84c3dd2IDad9fs5qc8xrma0cmk68t66am9rStatusSucceededSourceAPIHardwareH100Total durationCreatedInput
- seed
- 12345
- steps
- 50
- width
- 640
- height
- 360
- prompt
- A video in the style of THMTR, THMTR The video clip features a large owl perched on a metal stand. The owl is positioned in the foreground, with its body facing slightly to the left. The owl's feathers are predominantly dark brown with lighter brown and white streaks, giving it a mottled appearance. Its eyes are large and round, with a piercing gaze that seems to be directed towards something off-camera. The background is dark and somewhat blurred, suggesting a nighttime setting. The owl is set against a backdrop of a concrete wall or structure, which appears to be part of a larger, possibly industrial or urban environment. The wall has a rough texture and is illuminated by
- frame_rate
- 16
- num_frames
- 66
- lora_strength
- 1
- guidance_scale
- 6
{ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip features a large owl perched on a metal stand. The owl is positioned in the foreground, with its body facing slightly to the left. The owl's feathers are predominantly dark brown with lighter brown and white streaks, giving it a mottled appearance. Its eyes are large and round, with a piercing gaze that seems to be directed towards something off-camera.\nThe background is dark and somewhat blurred, suggesting a nighttime setting. The owl is set against a backdrop of a concrete wall or structure, which appears to be part of a larger, possibly industrial or urban environment. The wall has a rough texture and is illuminated by", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", { input: { seed: 12345, steps: 50, width: 640, height: 360, prompt: "A video in the style of THMTR, THMTR The video clip features a large owl perched on a metal stand. The owl is positioned in the foreground, with its body facing slightly to the left. The owl's feathers are predominantly dark brown with lighter brown and white streaks, giving it a mottled appearance. Its eyes are large and round, with a piercing gaze that seems to be directed towards something off-camera.\nThe background is dark and somewhat blurred, suggesting a nighttime setting. The owl is set against a backdrop of a concrete wall or structure, which appears to be part of a larger, possibly industrial or urban environment. The wall has a rough texture and is illuminated by", frame_rate: 16, num_frames: 66, lora_strength: 1, guidance_scale: 6 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", input={ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip features a large owl perched on a metal stand. The owl is positioned in the foreground, with its body facing slightly to the left. The owl's feathers are predominantly dark brown with lighter brown and white streaks, giving it a mottled appearance. Its eyes are large and round, with a piercing gaze that seems to be directed towards something off-camera.\nThe background is dark and somewhat blurred, suggesting a nighttime setting. The owl is set against a backdrop of a concrete wall or structure, which appears to be part of a larger, possibly industrial or urban environment. The wall has a rough texture and is illuminated by", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip features a large owl perched on a metal stand. The owl is positioned in the foreground, with its body facing slightly to the left. The owl\'s feathers are predominantly dark brown with lighter brown and white streaks, giving it a mottled appearance. Its eyes are large and round, with a piercing gaze that seems to be directed towards something off-camera.\\nThe background is dark and somewhat blurred, suggesting a nighttime setting. The owl is set against a backdrop of a concrete wall or structure, which appears to be part of a larger, possibly industrial or urban environment. The wall has a rough texture and is illuminated by", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-24T18:33:49.708189Z", "created_at": "2025-01-24T18:27:44.839000Z", "data_removed": false, "error": null, "id": "ad9fs5qc8xrma0cmk68t66am9r", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip features a large owl perched on a metal stand. The owl is positioned in the foreground, with its body facing slightly to the left. The owl's feathers are predominantly dark brown with lighter brown and white streaks, giving it a mottled appearance. Its eyes are large and round, with a piercing gaze that seems to be directed towards something off-camera.\nThe background is dark and somewhat blurred, suggesting a nighttime setting. The owl is set against a backdrop of a concrete wall or structure, which appears to be part of a larger, possibly industrial or urban environment. The wall has a rough texture and is illuminated by", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 }, "logs": "Seed set to: 12345\n⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements\n⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements\n�� USING REPLICATE WEIGHTS (preferred method)\n🎯 USING REPLICATE WEIGHTS TAR FILE 🎯\n----------------------------------------\n📦 Processing replicate weights tar file...\n🔄 Will rename LoRA to: replicate_5b10ec08-75dc-4a4a-978b-833236c904cd.safetensors\n📂 Extracting tar contents...\n✅ Found lora_comfyui.safetensors in tar\n✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_5b10ec08-75dc-4a4a-978b-833236c904cd.safetensors\n----------------------------------------\nChecking inputs\n====================================\nChecking weights\n✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae\n✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models\n====================================\nRunning workflow\n[ComfyUI] got prompt\nExecuting node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode\n[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 142\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77\nExecuting node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect\nExecuting node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader\n[ComfyUI] model_type FLOW\n[ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Using accelerate to load and assign model weights to device...\n[ComfyUI] Loading LoRA: replicate_5b10ec08-75dc-4a4a-978b-833236c904cd with strength: 1.0\n[ComfyUI] Requested to load HyVideoModel\n[ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True\n[ComfyUI] Input (height, width, video_length) = (368, 640, 65)\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps\n[ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['num_train_timesteps', 'n_tokens'])])\n[ComfyUI]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:53, 2.31s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.02s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.15s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.21s/it]\n[ComfyUI] 10%|█ | 5/50 [00:11<01:40, 2.24s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.26s/it]\n[ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.27s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.28s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.29s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.30s/it]\n[ComfyUI] 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2.31s/it]\n[ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it]\n[ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it]\n[ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it]\n[ComfyUI] 70%|███████ | 35/50 [01:20<00:34, 2.30s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.30s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.31s/it]\n[ComfyUI] 80%|████████ | 40/50 [01:31<00:23, 2.30s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.30s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.30s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it]\n[ComfyUI] 90%|█████████ | 45/50 [01:43<00:11, 2.30s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.30s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it]\n[ComfyUI] Allocated memory: memory=12.300 GB\n[ComfyUI] Max allocated memory: max_memory=15.099 GB\n[ComfyUI] Max reserved memory: max_reserved=16.281 GB\nExecuting node 5, title: HunyuanVideo Decode, class type: HyVideoDecode\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.48s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.25s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.28s/it]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.65it/s]\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.53it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.00it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.92it/s]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\nExecuting node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 63.73it/s]\n[ComfyUI] Prompt executed in 142.81 seconds\noutputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}}\n====================================\nHunyuanVideo_00001.png\nHunyuanVideo_00001.mp4", "metrics": { "predict_time": 149.291236618, "total_time": 364.869189 }, "output": "https://replicate.delivery/xezq/UETzQ8JfsLXHASfCQtIesogPNm3F9Dd4LKK6EjHIA4ia4xQoA/HunyuanVideo_00001.mp4", "started_at": "2025-01-24T18:31:20.416953Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-657z7gmvv7dqo3sopayibni4tzidf3m4dp3gkkezv7uyoeclcwha", "get": "https://api.replicate.com/v1/predictions/ad9fs5qc8xrma0cmk68t66am9r", "cancel": "https://api.replicate.com/v1/predictions/ad9fs5qc8xrma0cmk68t66am9r/cancel" }, "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9" }Generated inSeed set to: 12345 ⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements ⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements �� USING REPLICATE WEIGHTS (preferred method) 🎯 USING REPLICATE WEIGHTS TAR FILE 🎯 ---------------------------------------- 📦 Processing replicate weights tar file... 🔄 Will rename LoRA to: replicate_5b10ec08-75dc-4a4a-978b-833236c904cd.safetensors 📂 Extracting tar contents... ✅ Found lora_comfyui.safetensors in tar ✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_5b10ec08-75dc-4a4a-978b-833236c904cd.safetensors ---------------------------------------- Checking inputs ==================================== Checking weights ✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae ✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models ==================================== Running workflow [ComfyUI] got prompt Executing node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode [ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 142 [ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77 Executing node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect Executing node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader [ComfyUI] model_type FLOW [ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Using accelerate to load and assign model weights to device... [ComfyUI] Loading LoRA: replicate_5b10ec08-75dc-4a4a-978b-833236c904cd with strength: 1.0 [ComfyUI] Requested to load HyVideoModel [ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True [ComfyUI] Input (height, width, video_length) = (368, 640, 65) Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler [ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps [ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['num_train_timesteps', 'n_tokens'])]) [ComfyUI] [ComfyUI] 0%| | 0/50 [00:00<?, ?it/s] [ComfyUI] 2%|▏ | 1/50 [00:02<01:53, 2.31s/it] [ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.02s/it] [ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.15s/it] [ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.21s/it] [ComfyUI] 10%|█ | 5/50 [00:11<01:40, 2.24s/it] [ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.26s/it] [ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.27s/it] [ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.28s/it] [ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.29s/it] [ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it] [ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it] [ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.30s/it] [ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.30s/it] [ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.30s/it] [ComfyUI] 30%|███ | 15/50 [00:34<01:20, 2.30s/it] [ComfyUI] 32%|███▏ | 16/50 [00:36<01:18, 2.30s/it] [ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.30s/it] [ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.30s/it] [ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.30s/it] [ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.30s/it] [ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.30s/it] [ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.30s/it] [ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.30s/it] [ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.30s/it] [ComfyUI] 50%|█████ | 25/50 [00:57<00:57, 2.30s/it] [ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it] [ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.30s/it] [ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.30s/it] [ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.30s/it] [ComfyUI] 60%|██████ | 30/50 [01:08<00:46, 2.31s/it] [ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.31s/it] [ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.30s/it] [ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.30s/it] [ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.30s/it] [ComfyUI] 70%|███████ | 35/50 [01:20<00:34, 2.30s/it] [ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it] [ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it] [ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.30s/it] [ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.31s/it] [ComfyUI] 80%|████████ | 40/50 [01:31<00:23, 2.30s/it] [ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.30s/it] [ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.30s/it] [ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.30s/it] [ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.30s/it] [ComfyUI] 90%|█████████ | 45/50 [01:43<00:11, 2.30s/it] [ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it] [ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it] [ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.30s/it] [ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it] [ComfyUI] Allocated memory: memory=12.300 GB [ComfyUI] Max allocated memory: max_memory=15.099 GB [ComfyUI] Max reserved memory: max_reserved=16.281 GB Executing node 5, title: HunyuanVideo Decode, class type: HyVideoDecode [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.48s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.25s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.28s/it] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 25.65it/s] [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.53it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.00it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.92it/s] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 63.73it/s] [ComfyUI] Prompt executed in 142.81 seconds outputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}} ==================================== HunyuanVideo_00001.png HunyuanVideo_00001.mp4Prediction
deepfates/hunyuan-the-matrix-trilogy:e84c3dd2IDbsk4hg9hp9rm80cmk6mtjcax4gStatusSucceededSourceAPIHardwareH100Total durationCreatedInput
- seed
- 12345
- steps
- 50
- width
- 640
- height
- 360
- prompt
- A video in the style of THMTR, THMTR The video clip depicts two men walking down a dimly lit, narrow hallway. The hallway appears to be part of an industrial or institutional building, as evidenced by the concrete walls and ceiling. The lighting is minimal, with a single light fixture visible on the ceiling, casting shadows on the walls and creating a somewhat eerie atmosphere. The man in the foreground is wearing a dark suit and tie, while the man behind him is dressed in a lighter-colored suit. Both men are walking in the same direction, with the man in the foreground slightly ahead. The hallway is lined with pipes and other utility conduits, adding to the industrial feel of the
- frame_rate
- 16
- num_frames
- 66
- lora_strength
- 1
- guidance_scale
- 6
{ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts two men walking down a dimly lit, narrow hallway. The hallway appears to be part of an industrial or institutional building, as evidenced by the concrete walls and ceiling. The lighting is minimal, with a single light fixture visible on the ceiling, casting shadows on the walls and creating a somewhat eerie atmosphere.\nThe man in the foreground is wearing a dark suit and tie, while the man behind him is dressed in a lighter-colored suit. Both men are walking in the same direction, with the man in the foreground slightly ahead. The hallway is lined with pipes and other utility conduits, adding to the industrial feel of the", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", { input: { seed: 12345, steps: 50, width: 640, height: 360, prompt: "A video in the style of THMTR, THMTR The video clip depicts two men walking down a dimly lit, narrow hallway. The hallway appears to be part of an industrial or institutional building, as evidenced by the concrete walls and ceiling. The lighting is minimal, with a single light fixture visible on the ceiling, casting shadows on the walls and creating a somewhat eerie atmosphere.\nThe man in the foreground is wearing a dark suit and tie, while the man behind him is dressed in a lighter-colored suit. Both men are walking in the same direction, with the man in the foreground slightly ahead. The hallway is lined with pipes and other utility conduits, adding to the industrial feel of the", frame_rate: 16, num_frames: 66, lora_strength: 1, guidance_scale: 6 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", input={ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts two men walking down a dimly lit, narrow hallway. The hallway appears to be part of an industrial or institutional building, as evidenced by the concrete walls and ceiling. The lighting is minimal, with a single light fixture visible on the ceiling, casting shadows on the walls and creating a somewhat eerie atmosphere.\nThe man in the foreground is wearing a dark suit and tie, while the man behind him is dressed in a lighter-colored suit. Both men are walking in the same direction, with the man in the foreground slightly ahead. The hallway is lined with pipes and other utility conduits, adding to the industrial feel of the", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts two men walking down a dimly lit, narrow hallway. The hallway appears to be part of an industrial or institutional building, as evidenced by the concrete walls and ceiling. The lighting is minimal, with a single light fixture visible on the ceiling, casting shadows on the walls and creating a somewhat eerie atmosphere.\\nThe man in the foreground is wearing a dark suit and tie, while the man behind him is dressed in a lighter-colored suit. Both men are walking in the same direction, with the man in the foreground slightly ahead. The hallway is lined with pipes and other utility conduits, adding to the industrial feel of the", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-24T18:58:21.287895Z", "created_at": "2025-01-24T18:53:09.938000Z", "data_removed": false, "error": null, "id": "bsk4hg9hp9rm80cmk6mtjcax4g", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts two men walking down a dimly lit, narrow hallway. The hallway appears to be part of an industrial or institutional building, as evidenced by the concrete walls and ceiling. The lighting is minimal, with a single light fixture visible on the ceiling, casting shadows on the walls and creating a somewhat eerie atmosphere.\nThe man in the foreground is wearing a dark suit and tie, while the man behind him is dressed in a lighter-colored suit. Both men are walking in the same direction, with the man in the foreground slightly ahead. The hallway is lined with pipes and other utility conduits, adding to the industrial feel of the", "frame_rate": 16, "num_frames": 66, "lora_strength": 1, "guidance_scale": 6 }, "logs": "Seed set to: 12345\n⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements\n⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements\n�� USING REPLICATE WEIGHTS (preferred method)\n🎯 USING REPLICATE WEIGHTS TAR FILE 🎯\n----------------------------------------\n📦 Processing replicate weights tar file...\n🔄 Will rename LoRA to: replicate_fe6e69ad-a3f4-4199-8812-7c8e6014bab7.safetensors\n📂 Extracting tar contents...\n✅ Found lora_comfyui.safetensors in tar\n✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_fe6e69ad-a3f4-4199-8812-7c8e6014bab7.safetensors\n----------------------------------------\nChecking inputs\n====================================\nChecking weights\n✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models\n✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae\n====================================\nRunning workflow\n[ComfyUI] got prompt\nExecuting node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode\n[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 142\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77\nExecuting node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect\nExecuting node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader\n[ComfyUI] model_type FLOW\n[ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Using accelerate to load and assign model weights to device...\n[ComfyUI] Loading LoRA: replicate_fe6e69ad-a3f4-4199-8812-7c8e6014bab7 with strength: 1.0\n[ComfyUI] Requested to load HyVideoModel\n[ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True\n[ComfyUI] Input (height, width, video_length) = (368, 640, 65)\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps\n[ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['num_train_timesteps', 'n_tokens'])])\n[ComfyUI]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:52, 2.30s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.01s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.14s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.20s/it]\n[ComfyUI] 10%|█ | 5/50 [00:10<01:40, 2.23s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.25s/it]\n[ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.26s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.27s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.28s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.28s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:26, 2.29s/it]\n[ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.29s/it]\n[ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.29s/it]\n[ComfyUI] 30%|███ | 15/50 [00:33<01:20, 2.29s/it]\n[ComfyUI] 32%|███▏ | 16/50 [00:36<01:17, 2.29s/it]\n[ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.29s/it]\n[ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.29s/it]\n[ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.29s/it]\n[ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.29s/it]\n[ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.29s/it]\n[ComfyUI] 44%|████▍ | 22/50 [00:49<01:04, 2.29s/it]\n[ComfyUI] 46%|████▌ | 23/50 [00:52<01:01, 2.29s/it]\n[ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.29s/it]\n[ComfyUI] 50%|█████ | 25/50 [00:56<00:57, 2.29s/it]\n[ComfyUI] 52%|█████▏ | 26/50 [00:59<00:54, 2.29s/it]\n[ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.29s/it]\n[ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.29s/it]\n[ComfyUI] 58%|█████▊ | 29/50 [01:05<00:48, 2.29s/it]\n[ComfyUI] 60%|██████ | 30/50 [01:08<00:45, 2.29s/it]\n[ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.29s/it]\n[ComfyUI] 64%|██████▍ | 32/50 [01:12<00:41, 2.29s/it]\n[ComfyUI] 66%|██████▌ | 33/50 [01:15<00:38, 2.29s/it]\n[ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.29s/it]\n[ComfyUI] 70%|███████ | 35/50 [01:19<00:34, 2.29s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.29s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.29s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.29s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:28<00:25, 2.29s/it]\n[ComfyUI] 80%|████████ | 40/50 [01:31<00:22, 2.29s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.29s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [01:35<00:18, 2.29s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.29s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.29s/it]\n[ComfyUI] 90%|█████████ | 45/50 [01:42<00:11, 2.29s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:44<00:09, 2.29s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.29s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.29s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:51<00:02, 2.29s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.28s/it]\n[ComfyUI] Allocated memory: memory=12.300 GB\n[ComfyUI] Max allocated memory: max_memory=15.099 GB\n[ComfyUI] Max reserved memory: max_reserved=16.281 GB\nExecuting node 5, title: HunyuanVideo Decode, class type: HyVideoDecode\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.46s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.24s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.27s/it]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 26.04it/s]\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.57it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.03it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.95it/s]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\nExecuting node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 64.82it/s]\n[ComfyUI] Prompt executed in 140.39 seconds\noutputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}}\n====================================\nHunyuanVideo_00001.png\nHunyuanVideo_00001.mp4", "metrics": { "predict_time": 152.04443815, "total_time": 311.349895 }, "output": "https://replicate.delivery/xezq/jsn6LPlwzcI7JZhQvyIFeUfVnRa9xvlW8Np24d4fFJOamyQoA/HunyuanVideo_00001.mp4", "started_at": "2025-01-24T18:55:49.243457Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-jw3gsktquoncuzrcce644cixrcb4m5utuytkugbdrtn3tfpsk2xq", "get": "https://api.replicate.com/v1/predictions/bsk4hg9hp9rm80cmk6mtjcax4g", "cancel": "https://api.replicate.com/v1/predictions/bsk4hg9hp9rm80cmk6mtjcax4g/cancel" }, "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9" }Generated inSeed set to: 12345 ⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements ⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements �� USING REPLICATE WEIGHTS (preferred method) 🎯 USING REPLICATE WEIGHTS TAR FILE 🎯 ---------------------------------------- 📦 Processing replicate weights tar file... 🔄 Will rename LoRA to: replicate_fe6e69ad-a3f4-4199-8812-7c8e6014bab7.safetensors 📂 Extracting tar contents... ✅ Found lora_comfyui.safetensors in tar ✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_fe6e69ad-a3f4-4199-8812-7c8e6014bab7.safetensors ---------------------------------------- Checking inputs ==================================== Checking weights ✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models ✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae ==================================== Running workflow [ComfyUI] got prompt Executing node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode [ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 142 [ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77 Executing node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect Executing node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader [ComfyUI] model_type FLOW [ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Using accelerate to load and assign model weights to device... [ComfyUI] Loading LoRA: replicate_fe6e69ad-a3f4-4199-8812-7c8e6014bab7 with strength: 1.0 [ComfyUI] Requested to load HyVideoModel [ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True [ComfyUI] Input (height, width, video_length) = (368, 640, 65) Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler [ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps [ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['num_train_timesteps', 'n_tokens'])]) [ComfyUI] [ComfyUI] 0%| | 0/50 [00:00<?, ?it/s] [ComfyUI] 2%|▏ | 1/50 [00:02<01:52, 2.30s/it] [ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.01s/it] [ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.14s/it] [ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.20s/it] [ComfyUI] 10%|█ | 5/50 [00:10<01:40, 2.23s/it] [ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.25s/it] [ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.26s/it] [ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.27s/it] [ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.28s/it] [ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.28s/it] [ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it] [ComfyUI] 24%|██▍ | 12/50 [00:27<01:26, 2.29s/it] [ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.29s/it] [ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.29s/it] [ComfyUI] 30%|███ | 15/50 [00:33<01:20, 2.29s/it] [ComfyUI] 32%|███▏ | 16/50 [00:36<01:17, 2.29s/it] [ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.29s/it] [ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.29s/it] [ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.29s/it] [ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.29s/it] [ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.29s/it] [ComfyUI] 44%|████▍ | 22/50 [00:49<01:04, 2.29s/it] [ComfyUI] 46%|████▌ | 23/50 [00:52<01:01, 2.29s/it] [ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.29s/it] [ComfyUI] 50%|█████ | 25/50 [00:56<00:57, 2.29s/it] [ComfyUI] 52%|█████▏ | 26/50 [00:59<00:54, 2.29s/it] [ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.29s/it] [ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.29s/it] [ComfyUI] 58%|█████▊ | 29/50 [01:05<00:48, 2.29s/it] [ComfyUI] 60%|██████ | 30/50 [01:08<00:45, 2.29s/it] [ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.29s/it] [ComfyUI] 64%|██████▍ | 32/50 [01:12<00:41, 2.29s/it] [ComfyUI] 66%|██████▌ | 33/50 [01:15<00:38, 2.29s/it] [ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.29s/it] [ComfyUI] 70%|███████ | 35/50 [01:19<00:34, 2.29s/it] [ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.29s/it] [ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.29s/it] [ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.29s/it] [ComfyUI] 78%|███████▊ | 39/50 [01:28<00:25, 2.29s/it] [ComfyUI] 80%|████████ | 40/50 [01:31<00:22, 2.29s/it] [ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.29s/it] [ComfyUI] 84%|████████▍ | 42/50 [01:35<00:18, 2.29s/it] [ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.29s/it] [ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.29s/it] [ComfyUI] 90%|█████████ | 45/50 [01:42<00:11, 2.29s/it] [ComfyUI] 92%|█████████▏| 46/50 [01:44<00:09, 2.29s/it] [ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.29s/it] [ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.29s/it] [ComfyUI] 98%|█████████▊| 49/50 [01:51<00:02, 2.29s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.28s/it] [ComfyUI] Allocated memory: memory=12.300 GB [ComfyUI] Max allocated memory: max_memory=15.099 GB [ComfyUI] Max reserved memory: max_reserved=16.281 GB Executing node 5, title: HunyuanVideo Decode, class type: HyVideoDecode [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.46s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.24s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.27s/it] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 26.04it/s] [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.57it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.03it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.95it/s] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 64.82it/s] [ComfyUI] Prompt executed in 140.39 seconds outputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}} ==================================== HunyuanVideo_00001.png HunyuanVideo_00001.mp4Prediction
deepfates/hunyuan-the-matrix-trilogy:e84c3dd2IDegdsjtywqhrmc0cmn4qsgfkpmcStatusSucceededSourceAPIHardwareH100Total durationCreatedInput
- seed
- 12345
- steps
- 50
- width
- 640
- height
- 360
- prompt
- A video in the style of THMTR, THMTR The video clip depicts A warrior woman with long dark hair standing on a cliff edge, her black cloak billowing in the storm wind
- frame_rate
- 16
- num_frames
- 66
- lora_strength
- 1.2
- guidance_scale
- 6
{ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts A warrior woman with long dark hair standing on a cliff edge, her black cloak billowing in the storm wind", "frame_rate": 16, "num_frames": 66, "lora_strength": 1.2, "guidance_scale": 6 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", { input: { seed: 12345, steps: 50, width: 640, height: 360, prompt: "A video in the style of THMTR, THMTR The video clip depicts A warrior woman with long dark hair standing on a cliff edge, her black cloak billowing in the storm wind", frame_rate: 16, num_frames: 66, lora_strength: 1.2, guidance_scale: 6 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", input={ "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts A warrior woman with long dark hair standing on a cliff edge, her black cloak billowing in the storm wind", "frame_rate": 16, "num_frames": 66, "lora_strength": 1.2, "guidance_scale": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts A warrior woman with long dark hair standing on a cliff edge, her black cloak billowing in the storm wind", "frame_rate": 16, "num_frames": 66, "lora_strength": 1.2, "guidance_scale": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-27T19:17:08.743616Z", "created_at": "2025-01-27T19:14:33.788000Z", "data_removed": false, "error": null, "id": "egdsjtywqhrmc0cmn4qsgfkpmc", "input": { "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of THMTR, THMTR The video clip depicts A warrior woman with long dark hair standing on a cliff edge, her black cloak billowing in the storm wind", "frame_rate": 16, "num_frames": 66, "lora_strength": 1.2, "guidance_scale": 6 }, "logs": "Seed set to: 12345\n⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements\n⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements\n�� USING REPLICATE WEIGHTS (preferred method)\n🎯 USING REPLICATE WEIGHTS TAR FILE 🎯\n----------------------------------------\n📦 Processing replicate weights tar file...\n🔄 Will rename LoRA to: replicate_b64c156c-c15e-44bf-a4f9-48576e161f04.safetensors\n📂 Extracting tar contents...\n✅ Found lora_comfyui.safetensors in tar\n✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_b64c156c-c15e-44bf-a4f9-48576e161f04.safetensors\n----------------------------------------\nChecking inputs\n====================================\nChecking weights\n✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models\n✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae\n====================================\nRunning workflow\n[ComfyUI] got prompt\nExecuting node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode\n[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 40\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 39\nExecuting node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect\nExecuting node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader\n[ComfyUI] model_type FLOW\n[ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Using accelerate to load and assign model weights to device...\n[ComfyUI] Loading LoRA: replicate_b64c156c-c15e-44bf-a4f9-48576e161f04 with strength: 1.2\n[ComfyUI] Requested to load HyVideoModel\n[ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True\n[ComfyUI] Input (height, width, video_length) = (368, 640, 65)\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps\n[ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['n_tokens', 'num_train_timesteps'])])\n[ComfyUI]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:52, 2.29s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.01s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.14s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.20s/it]\n[ComfyUI] 10%|█ | 5/50 [00:10<01:40, 2.23s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.25s/it]\n[ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.27s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.27s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.28s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.28s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:26, 2.29s/it]\n[ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.29s/it]\n[ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.29s/it]\n[ComfyUI] 30%|███ | 15/50 [00:33<01:20, 2.29s/it]\n[ComfyUI] 32%|███▏ | 16/50 [00:36<01:17, 2.29s/it]\n[ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.29s/it]\n[ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.29s/it]\n[ComfyUI] 38%|███▊ | 19/50 [00:43<01:10, 2.29s/it]\n[ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.29s/it]\n[ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.29s/it]\n[ComfyUI] 44%|████▍ | 22/50 [00:49<01:04, 2.29s/it]\n[ComfyUI] 46%|████▌ | 23/50 [00:52<01:01, 2.29s/it]\n[ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.29s/it]\n[ComfyUI] 50%|█████ | 25/50 [00:56<00:57, 2.29s/it]\n[ComfyUI] 52%|█████▏ | 26/50 [00:59<00:54, 2.29s/it]\n[ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.29s/it]\n[ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.29s/it]\n[ComfyUI] 58%|█████▊ | 29/50 [01:05<00:48, 2.29s/it]\n[ComfyUI] 60%|██████ | 30/50 [01:08<00:45, 2.29s/it]\n[ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.29s/it]\n[ComfyUI] 64%|██████▍ | 32/50 [01:12<00:41, 2.29s/it]\n[ComfyUI] 66%|██████▌ | 33/50 [01:15<00:38, 2.29s/it]\n[ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.29s/it]\n[ComfyUI] 70%|███████ | 35/50 [01:19<00:34, 2.29s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:21<00:32, 2.29s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.29s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.29s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:28<00:25, 2.29s/it]\n[ComfyUI] 80%|████████ | 40/50 [01:31<00:22, 2.29s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.29s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [01:35<00:18, 2.29s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.29s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.29s/it]\n[ComfyUI] 90%|█████████ | 45/50 [01:42<00:11, 2.29s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:44<00:09, 2.29s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.29s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.29s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:51<00:02, 2.29s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.28s/it]\n[ComfyUI] Allocated memory: memory=12.300 GB\n[ComfyUI] Max allocated memory: max_memory=15.099 GB\n[ComfyUI] Max reserved memory: max_reserved=16.344 GB\nExecuting node 5, title: HunyuanVideo Decode, class type: HyVideoDecode\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.46s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.24s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.28s/it]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 26.64it/s]\n[ComfyUI]\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.54it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.02it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.94it/s]\n[ComfyUI]\n[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]\nExecuting node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine\n[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 63.26it/s]\n[ComfyUI] Prompt executed in 143.19 seconds\noutputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}}\n====================================\nHunyuanVideo_00001.png\nHunyuanVideo_00001.mp4", "metrics": { "predict_time": 154.948066663, "total_time": 154.955616 }, "output": "https://replicate.delivery/xezq/tZZYudGaWnYlOF2YDzjPgflMwhgu8yqa1peC5p8x5I002YJUA/HunyuanVideo_00001.mp4", "started_at": "2025-01-27T19:14:33.795550Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bsvm-2ryojtfjkpja3u2kak3ghbcwlwxrgov2wql26vwjcxexhhjoxp3a", "get": "https://api.replicate.com/v1/predictions/egdsjtywqhrmc0cmn4qsgfkpmc", "cancel": "https://api.replicate.com/v1/predictions/egdsjtywqhrmc0cmn4qsgfkpmc/cancel" }, "version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9" }Generated inSeed set to: 12345 ⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements ⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements �� USING REPLICATE WEIGHTS (preferred method) 🎯 USING REPLICATE WEIGHTS TAR FILE 🎯 ---------------------------------------- 📦 Processing replicate weights tar file... 🔄 Will rename LoRA to: replicate_b64c156c-c15e-44bf-a4f9-48576e161f04.safetensors 📂 Extracting tar contents... ✅ Found lora_comfyui.safetensors in tar ✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_b64c156c-c15e-44bf-a4f9-48576e161f04.safetensors ---------------------------------------- Checking inputs ==================================== Checking weights ✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models ✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae ==================================== Running workflow [ComfyUI] got prompt Executing node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode [ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 40 [ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 39 Executing node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect Executing node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader [ComfyUI] model_type FLOW [ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Using accelerate to load and assign model weights to device... [ComfyUI] Loading LoRA: replicate_b64c156c-c15e-44bf-a4f9-48576e161f04 with strength: 1.2 [ComfyUI] Requested to load HyVideoModel [ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True [ComfyUI] Input (height, width, video_length) = (368, 640, 65) Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler [ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. [ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps [ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['n_tokens', 'num_train_timesteps'])]) [ComfyUI] [ComfyUI] 0%| | 0/50 [00:00<?, ?it/s] [ComfyUI] 2%|▏ | 1/50 [00:02<01:52, 2.29s/it] [ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.01s/it] [ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.14s/it] [ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.20s/it] [ComfyUI] 10%|█ | 5/50 [00:10<01:40, 2.23s/it] [ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.25s/it] [ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.27s/it] [ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.27s/it] [ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.28s/it] [ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.28s/it] [ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it] [ComfyUI] 24%|██▍ | 12/50 [00:27<01:26, 2.29s/it] [ComfyUI] 26%|██▌ | 13/50 [00:29<01:24, 2.29s/it] [ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.29s/it] [ComfyUI] 30%|███ | 15/50 [00:33<01:20, 2.29s/it] [ComfyUI] 32%|███▏ | 16/50 [00:36<01:17, 2.29s/it] [ComfyUI] 34%|███▍ | 17/50 [00:38<01:15, 2.29s/it] [ComfyUI] 36%|███▌ | 18/50 [00:40<01:13, 2.29s/it] [ComfyUI] 38%|███▊ | 19/50 [00:43<01:10, 2.29s/it] [ComfyUI] 40%|████ | 20/50 [00:45<01:08, 2.29s/it] [ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.29s/it] [ComfyUI] 44%|████▍ | 22/50 [00:49<01:04, 2.29s/it] [ComfyUI] 46%|████▌ | 23/50 [00:52<01:01, 2.29s/it] [ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.29s/it] [ComfyUI] 50%|█████ | 25/50 [00:56<00:57, 2.29s/it] [ComfyUI] 52%|█████▏ | 26/50 [00:59<00:54, 2.29s/it] [ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.29s/it] [ComfyUI] 56%|█████▌ | 28/50 [01:03<00:50, 2.29s/it] [ComfyUI] 58%|█████▊ | 29/50 [01:05<00:48, 2.29s/it] [ComfyUI] 60%|██████ | 30/50 [01:08<00:45, 2.29s/it] [ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.29s/it] [ComfyUI] 64%|██████▍ | 32/50 [01:12<00:41, 2.29s/it] [ComfyUI] 66%|██████▌ | 33/50 [01:15<00:38, 2.29s/it] [ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.29s/it] [ComfyUI] 70%|███████ | 35/50 [01:19<00:34, 2.29s/it] [ComfyUI] 72%|███████▏ | 36/50 [01:21<00:32, 2.29s/it] [ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.29s/it] [ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.29s/it] [ComfyUI] 78%|███████▊ | 39/50 [01:28<00:25, 2.29s/it] [ComfyUI] 80%|████████ | 40/50 [01:31<00:22, 2.29s/it] [ComfyUI] 82%|████████▏ | 41/50 [01:33<00:20, 2.29s/it] [ComfyUI] 84%|████████▍ | 42/50 [01:35<00:18, 2.29s/it] [ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.29s/it] [ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.29s/it] [ComfyUI] 90%|█████████ | 45/50 [01:42<00:11, 2.29s/it] [ComfyUI] 92%|█████████▏| 46/50 [01:44<00:09, 2.29s/it] [ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.29s/it] [ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.29s/it] [ComfyUI] 98%|█████████▊| 49/50 [01:51<00:02, 2.29s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it] [ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.28s/it] [ComfyUI] Allocated memory: memory=12.300 GB [ComfyUI] Max allocated memory: max_memory=15.099 GB [ComfyUI] Max reserved memory: max_reserved=16.344 GB Executing node 5, title: HunyuanVideo Decode, class type: HyVideoDecode [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.46s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.24s/it] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.28s/it] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 26.64it/s] [ComfyUI] [ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s] [ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:00<00:00, 2.54it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 3.02it/s] [ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.94it/s] [ComfyUI] [ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s] Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine [ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 63.26it/s] [ComfyUI] Prompt executed in 143.19 seconds outputs: {'34': {'gifs': [{'filename': 'HunyuanVideo_00001.mp4', 'subfolder': '', 'type': 'output', 'format': 'video/h264-mp4', 'frame_rate': 16.0, 'workflow': 'HunyuanVideo_00001.png', 'fullpath': '/tmp/outputs/HunyuanVideo_00001.mp4'}]}} ==================================== HunyuanVideo_00001.png HunyuanVideo_00001.mp4
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