deepfates/hunyuan-blade-runner-2049:5c4ea69d | Run with an API on Replicate

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deepfates /hunyuan-blade-runner-2049:5c4ea69d

Playground API

Input

prompt

string

Shift + Return to add a new line

A video in the style of PXR, PXR 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 onA video in the style of PXR, PXR 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

The text prompt describing your video scene.

Default: ""

lora_url

string

Shift + Return to add a new line

A URL pointing to your LoRA .safetensors file or a Hugging Face repo (e.g. 'user/repo' - uses the first .safetensors file).

Default: ""

lora_strength

number

(minimum: -10, maximum: 10)

Scale/strength for your LoRA.

Default: 1

scheduler

string

Algorithm used to generate the video frames.

Default: "DPMSolverMultistepScheduler"

steps

integer

(minimum: 1, maximum: 150)

Number of diffusion steps.

Default: 50

guidance_scale

number

(minimum: 0, maximum: 30)

Overall influence of text vs. model.

Default: 6

flow_shift

integer

(minimum: 0, maximum: 20)

Video continuity factor (flow).

Default: 9

num_frames

integer

(minimum: 1, maximum: 1440)

How many frames (duration) in the resulting video.

Default: 33

width

integer

(minimum: 64, maximum: 1536)

Width for the generated video.

Default: 640

height

integer

(minimum: 64, maximum: 1024)

Height for the generated video.

Default: 360

denoise_strength

number

(minimum: 0, maximum: 2)

Controls how strongly noise is applied each step.

Default: 1

force_offload

boolean

Whether to force model layers offloaded to CPU.

Default: true

frame_rate

integer

(minimum: 1, maximum: 60)

Video frame rate.

Default: 16

crf

integer

(minimum: 0, maximum: 51)

CRF (quality) for H264 encoding. Lower values = higher quality.

Default: 19

enhance_weight

number

(minimum: 0, maximum: 2)

Strength of the video enhancement effect.

Default: 0.3

enhance_single

boolean

Apply enhancement to individual frames.

Default: true

enhance_double

boolean

Apply enhancement across frame pairs.

Default: true

enhance_start

number

(minimum: 0, maximum: 1)

When to start enhancement in the video. Must be less than enhance_end.

Default: 0

enhance_end

number

(minimum: 0, maximum: 1)

When to end enhancement in the video. Must be greater than enhance_start.

Default: 1

seed

integer

Set a seed for reproducibility. Random by default.

Run this model in Node.js with one line of code:

npx create-replicate --model=deepfates/hunyuan-blade-runner-2049

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment 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";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run deepfates/hunyuan-blade-runner-2049 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "deepfates/hunyuan-blade-runner-2049:5c4ea69d26b3a4611f4929e9267ff916d132e55afb08ae6dd84fb8c98511ac69",
  {
    input: {
      crf: 19,
      seed: 12345,
      steps: 50,
      width: 640,
      height: 360,
      prompt: "A video in the style of PXR, PXR 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.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run deepfates/hunyuan-blade-runner-2049 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "deepfates/hunyuan-blade-runner-2049:5c4ea69d26b3a4611f4929e9267ff916d132e55afb08ae6dd84fb8c98511ac69",
    input={
        "crf": 19,
        "seed": 12345,
        "steps": 50,
        "width": 640,
        "height": 360,
        "prompt": "A video in the style of PXR, PXR 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 the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run deepfates/hunyuan-blade-runner-2049 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-blade-runner-2049:5c4ea69d26b3a4611f4929e9267ff916d132e55afb08ae6dd84fb8c98511ac69",
    "input": {
      "crf": 19,
      "seed": 12345,
      "steps": 50,
      "width": 640,
      "height": 360,
      "prompt": "A video in the style of PXR, PXR 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.

You can run this model locally using Cog. First, install Cog:

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-blade-runner-2049@sha256:5c4ea69d26b3a4611f4929e9267ff916d132e55afb08ae6dd84fb8c98511ac69 \
  -i 'crf=19' \
  -i 'seed=12345' \
  -i 'steps=50' \
  -i 'width=640' \
  -i 'height=360' \
  -i $'prompt="A video in the style of PXR, PXR 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-blade-runner-2049@sha256:5c4ea69d26b3a4611f4929e9267ff916d132e55afb08ae6dd84fb8c98511ac69
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 PXR, PXR 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.

Output

{
  "completed_at": "2025-01-24T01:56:17.677290Z",
  "created_at": "2025-01-24T01:00:22.234000Z",
  "data_removed": false,
  "error": null,
  "id": "dfwhqz05b9rmc0cmjq9tp4cezw",
  "input": {
    "crf": 19,
    "seed": 12345,
    "steps": 50,
    "width": 640,
    "height": 360,
    "prompt": "A video in the style of PXR, PXR 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,  2.14s/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=15.099 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, 25.87it/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, 65.23it/s]\n[ComfyUI] Prompt executed in 133.31 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": 135.580034209,
    "total_time": 3355.44329
  },
  "output": "https://replicate.delivery/xezq/RlL8PJl0oJa9HF8hVwEUG10yfP7QDAffHHomQVOkQr1DqUQoA/HunyuanVideo_00001.mp4",
  "started_at": "2025-01-24T01:54:02.097256Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bsvm-opezuq754twebv2gyey6try3ypgvniyyknfvm4mik74724vltrja",
    "get": "https://api.replicate.com/v1/predictions/dfwhqz05b9rmc0cmjq9tp4cezw",
    "cancel": "https://api.replicate.com/v1/predictions/dfwhqz05b9rmc0cmjq9tp4cezw/cancel"
  },
  "version": "5c4ea69d26b3a4611f4929e9267ff916d132e55afb08ae6dd84fb8c98511ac69"
}

Generated in

2 minutes 16 seconds

Tweak it ShareReport View full prediction

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,  2.14s/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=15.099 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,  1.46s/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, 25.87it/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, 65.23it/s]
[ComfyUI] Prompt executed in 133.31 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