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deepfates /hunyuan-twin-peaks:9a578855
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run deepfates/hunyuan-twin-peaks using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"deepfates/hunyuan-twin-peaks:9a578855228e41283cf23df1af710f71490e3bf9503bb0baaa485fa8c08bf2a6",
{
input: {
crf: 19,
seed: 12345,
steps: 50,
width: 640,
height: 360,
prompt: "A video in the style of TWNPK, TWNPK 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
}
}
);
// To access the file URL:
console.log(output.url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run deepfates/hunyuan-twin-peaks using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"deepfates/hunyuan-twin-peaks:9a578855228e41283cf23df1af710f71490e3bf9503bb0baaa485fa8c08bf2a6",
input={
"crf": 19,
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of TWNPK, TWNPK 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.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run deepfates/hunyuan-twin-peaks 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": "deepfates/hunyuan-twin-peaks:9a578855228e41283cf23df1af710f71490e3bf9503bb0baaa485fa8c08bf2a6",
"input": {
"crf": 19,
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of TWNPK, TWNPK 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/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/deepfates/hunyuan-twin-peaks@sha256:9a578855228e41283cf23df1af710f71490e3bf9503bb0baaa485fa8c08bf2a6 \
-i 'crf=19' \
-i 'seed=12345' \
-i 'steps=50' \
-i 'width=640' \
-i 'height=360' \
-i $'prompt="A video in the style of TWNPK, TWNPK 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"' \
-i 'lora_url=""' \
-i 'scheduler="DPMSolverMultistepScheduler"' \
-i 'flow_shift=9' \
-i 'frame_rate=16' \
-i 'num_frames=66' \
-i 'enhance_end=1' \
-i 'enhance_start=0' \
-i 'force_offload=true' \
-i 'lora_strength=1' \
-i 'enhance_double=true' \
-i 'enhance_single=true' \
-i 'enhance_weight=0.3' \
-i 'guidance_scale=6' \
-i 'denoise_strength=1'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/deepfates/hunyuan-twin-peaks@sha256:9a578855228e41283cf23df1af710f71490e3bf9503bb0baaa485fa8c08bf2a6
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "crf": 19, "seed": 12345, "steps": 50, "width": 640, "height": 360, "prompt": "A video in the style of TWNPK, TWNPK 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 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
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Output
{
"completed_at": "2025-01-24T00:11:35.703962Z",
"created_at": "2025-01-24T00:03:01.778000Z",
"data_removed": false,
"error": null,
"id": "4d2d0d4629rme0cmjpfanznrt8",
"input": {
"crf": 19,
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of TWNPK, TWNPK 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_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: 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<01:52, 2.30s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:36, 2.02s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:40, 2.15s/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, 2.30s/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 [00:40<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<00:53, 2.31s/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, 2.31s/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, 2.30s/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, 2.31s/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 [01:33<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, 2.31s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.31s/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, 2.31s/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, 2.29s/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=16.344 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, 25.78it/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, 3.00it/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, 65.10it/s]\n[ComfyUI] Prompt executed in 134.47 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": 139.639128155,
"total_time": 513.925962
},
"output": "https://replicate.delivery/xezq/hHCfK5iMwG2tSyXRb3fbElFdXLeuBz4dyTlcy7RlNjNvlRQoA/HunyuanVideo_00001.mp4",
"started_at": "2025-01-24T00:09:16.064834Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bsvm-m4xkx2pmcsdirskw2un7vwislhzj35gsek7k5pw6vxawx4ubgusq",
"get": "https://api.replicate.com/v1/predictions/4d2d0d4629rme0cmjpfanznrt8",
"cancel": "https://api.replicate.com/v1/predictions/4d2d0d4629rme0cmjpfanznrt8/cancel"
},
"version": "9a578855228e41283cf23df1af710f71490e3bf9503bb0baaa485fa8c08bf2a6"
}
Seed 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: 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<01:52, 2.30s/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, 2.30s/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 [00:40<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<00:53, 2.31s/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, 2.31s/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, 2.30s/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, 2.31s/it]
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[ComfyUI] 80%|████████ | 40/50 [01:31<00:23, 2.31s/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, 2.31s/it]
[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.31s/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, 2.31s/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, 2.29s/it]
[ComfyUI] Allocated memory: memory=12.300 GB
[ComfyUI] Max allocated memory: max_memory=15.099 GB
[ComfyUI] Max reserved memory: max_reserved=16.344 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, 25.78it/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, 3.00it/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, 65.10it/s]
[ComfyUI] Prompt executed in 134.47 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