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Hunyuan-Video model finetuned on Spider-Man: Into the Spider-Verse (2018). Trigger word is "SPDRV". Use "A video in the style of SPDRV, SPDRV" at the beginning of your prompt for best results.
A fashion model
A fine-tuned FLUX.1 model. Use trigger word "ZUCK". Created with ReFlux (https://reflux.replicate.dev).
FLUX lora based on the game Baldur's Gate 3
A FLUX model fine-tuned on fallenchungus comics
Hunyuan-Video model finetuned on Game of Thrones (2011). Trigger word is "GMFTH". Use "A video in the style of GMFTH, GMFTH" at the beginning of your prompt for best results
Hunyuan-Video model finetuned on La La Land (2016). Trigger word is "LLLND". Use "A video in the style of LLLND, LLLND" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on Blade Runner 2049 (2017). Trigger word is "BLDRN". Use "A video in the style of BLDRN, BLDRN" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on Arcane (2021). Trigger word is "RCN". Use "A video in the style of RCN, RCN" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on The Lord of the Rings Trilogy (2001). Trigger word is "THLRD". Use "A video in the style of THLRD, THLRD" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on The Grand Budapest Hotel (2014). Trigger word is "THGRN". Use "A video in the style of THGRN, THGRN" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on Pixar Films (1995). Trigger word is "PXR". Use "A video in the style of PXR, PXR" at the beginning of your prompt for best results.
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.
Hunyuan-Video model finetuned on Indiana Jones Series (1981). Trigger word is "NDNJN". Use "A video in the style of NDNJN, NDNJN" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on Joker (2019). Trigger word is "JKR". Use "A video in the style of JKR, JKR" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on Blade Runner (1982). Trigger word is "BLDRN". Use "A video in the style of BLDRN, BLDRN" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on Inception (2010). Trigger word is "NCPTN". Use "A video in the style of NCPTN, NCPTN" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on Pulp Fiction (1994). Trigger word is "PLPFC". Use "A video in the style of PLPFC, PLPFC" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on Spider-Man: Into the Spider-Verse (2018). Trigger word is "SPDRM". Use "A video in the style of SPDRM, SPDRM" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on Her (2013). Trigger word is "HR". Use "A video in the style of HR, HR" at the beginning of your prompt for best results.
Hunyuan-Video model finetuned on Spider-Man: Into the Spider-Verse (2018). Trigger word is "SPDRV". Use "A video in the style of SPDRV, SPDRV" at the beginning of your prompt for best results.
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";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run deepfates/hunyuan-spiderverse using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"deepfates/hunyuan-spiderverse:0149fb2019d637f6b3a610c68b04c84b629f71b8d1b838960147f8e8cca705c5",
{
input: {
crf: 19,
seed: 12345,
steps: 50,
width: 640,
height: 360,
prompt: "A video in the style of SPDRV, SPDRV 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
}
}
);
// 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-spiderverse using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"deepfates/hunyuan-spiderverse:0149fb2019d637f6b3a610c68b04c84b629f71b8d1b838960147f8e8cca705c5",
input={
"crf": 19,
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of SPDRV, SPDRV 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
}
)
# To access the file URL:
print(output.url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output.read())
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-spiderverse 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-spiderverse:0149fb2019d637f6b3a610c68b04c84b629f71b8d1b838960147f8e8cca705c5",
"input": {
"crf": 19,
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of SPDRV, SPDRV 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/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-spiderverse@sha256:0149fb2019d637f6b3a610c68b04c84b629f71b8d1b838960147f8e8cca705c5 \
-i 'crf=19' \
-i 'seed=12345' \
-i 'steps=50' \
-i 'width=640' \
-i 'height=360' \
-i $'prompt="A video in the style of SPDRV, SPDRV 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"' \
-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-spiderverse@sha256:0149fb2019d637f6b3a610c68b04c84b629f71b8d1b838960147f8e8cca705c5
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 SPDRV, SPDRV 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 } }' \ 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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{
"completed_at": "2025-01-24T00:30:24.223797Z",
"created_at": "2025-01-24T00:25:10.342000Z",
"data_removed": false,
"error": null,
"id": "az2qqepbrsrmc0cmjps88575r0",
"input": {
"crf": 19,
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of SPDRV, SPDRV 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: 144\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, 2.01s/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, 2.28s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.29s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.29s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/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 [00:34<01:20, 2.29s/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<01:01, 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=15.099 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, 1.46s/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, 25.82it/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, 64.77it/s]\n[ComfyUI] Prompt executed in 133.05 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": 150.154655949,
"total_time": 313.881797
},
"output": "https://replicate.delivery/xezq/XyXpwMLXlL57HpVfhiAbnISkQjolczdsHYieWlAf4UDBJSQoA/HunyuanVideo_00001.mp4",
"started_at": "2025-01-24T00:27:54.069141Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bsvm-k7lqsy2jgty2yf5ksonpmorfyehnydfyhwohbzdoxat43vbwsmcq",
"get": "https://api.replicate.com/v1/predictions/az2qqepbrsrmc0cmjps88575r0",
"cancel": "https://api.replicate.com/v1/predictions/az2qqepbrsrmc0cmjps88575r0/cancel"
},
"version": "0149fb2019d637f6b3a610c68b04c84b629f71b8d1b838960147f8e8cca705c5"
}
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_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: 144
[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, 2.01s/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, 2.28s/it]
[ComfyUI] 16%|█▌ | 8/50 [00:17<01:35, 2.29s/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]
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[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]
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[ComfyUI]
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Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine
[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 64.77it/s]
[ComfyUI] Prompt executed in 133.05 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
This model costs approximately $0.63 to run on Replicate, or 1 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.
This model runs on Nvidia H100 GPU hardware. Predictions typically complete within 7 minutes. The predict time for this model varies significantly based on the inputs.
This model doesn't have a readme.
This model is not yet booted but ready for API calls. Your first API call will boot the model and may take longer, but after that subsequent responses will be fast.
This model costs approximately $0.63 to run on Replicate, but this varies depending on your inputs.
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_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: 144
[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
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[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]
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[ComfyUI]
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[ComfyUI]
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Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine
[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 64.77it/s]
[ComfyUI] Prompt executed in 133.05 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