fofr/hunyuan-homer-meme – Run with an API on Replicate

fofr / hunyuan-homer-meme

A Hunyuan fine-tuned on the Homer disappearing into a bush meme

Cold

Public
98 runs
H100
Fine-tune

Run with an API

Playground API Examples README Versions

Input

prompt

string

Shift + Return to add a new line

A Simpsons animation showing HOMER slowly backing away into green bushes until he is out of sightA Simpsons animation showing HOMER slowly backing away into green bushes until he is out of sight

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=fofr/hunyuan-homer-meme

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";

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

Run fofr/hunyuan-homer-meme using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/hunyuan-homer-meme:f0eab4bab4afa1d9d1484a21118bb7539babfac0a119dc41e5b1764a1ec1357b",
  {
    input: {
      crf: 19,
      steps: 50,
      width: 640,
      height: 360,
      prompt: "A Simpsons animation showing HOMER slowly backing away into green bushes until he is out of sight",
      lora_url: "",
      scheduler: "DPMSolverMultistepScheduler",
      flow_shift: 9,
      frame_rate: 24,
      num_frames: 85,
      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 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 fofr/hunyuan-homer-meme using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/hunyuan-homer-meme:f0eab4bab4afa1d9d1484a21118bb7539babfac0a119dc41e5b1764a1ec1357b",
    input={
        "crf": 19,
        "steps": 50,
        "width": 640,
        "height": 360,
        "prompt": "A Simpsons animation showing HOMER slowly backing away into green bushes until he is out of sight",
        "lora_url": "",
        "scheduler": "DPMSolverMultistepScheduler",
        "flow_shift": 9,
        "frame_rate": 24,
        "num_frames": 85,
        "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 fofr/hunyuan-homer-meme 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": "f0eab4bab4afa1d9d1484a21118bb7539babfac0a119dc41e5b1764a1ec1357b",
    "input": {
      "crf": 19,
      "steps": 50,
      "width": 640,
      "height": 360,
      "prompt": "A Simpsons animation showing HOMER slowly backing away into green bushes until he is out of sight",
      "lora_url": "",
      "scheduler": "DPMSolverMultistepScheduler",
      "flow_shift": 9,
      "frame_rate": 24,
      "num_frames": 85,
      "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/fofr/hunyuan-homer-meme@sha256:f0eab4bab4afa1d9d1484a21118bb7539babfac0a119dc41e5b1764a1ec1357b \
  -i 'crf=19' \
  -i 'steps=50' \
  -i 'width=640' \
  -i 'height=360' \
  -i 'prompt="A Simpsons animation showing HOMER slowly backing away into green bushes until he is out of sight"' \
  -i 'lora_url=""' \
  -i 'scheduler="DPMSolverMultistepScheduler"' \
  -i 'flow_shift=9' \
  -i 'frame_rate=24' \
  -i 'num_frames=85' \
  -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/fofr/hunyuan-homer-meme@sha256:f0eab4bab4afa1d9d1484a21118bb7539babfac0a119dc41e5b1764a1ec1357b
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "crf": 19,
      "steps": 50,
      "width": 640,
      "height": 360,
      "prompt": "A Simpsons animation showing HOMER slowly backing away into green bushes until he is out of sight",
      "lora_url": "",
      "scheduler": "DPMSolverMultistepScheduler",
      "flow_shift": 9,
      "frame_rate": 24,
      "num_frames": 85,
      "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": "2025-01-08T08:00:27.105310Z",
  "created_at": "2025-01-08T07:56:16.869000Z",
  "data_removed": false,
  "error": null,
  "id": "00pqh8rccnrmc0cm8knb0c69aw",
  "input": {
    "crf": 19,
    "steps": 50,
    "width": 640,
    "height": 360,
    "prompt": "A Simpsons animation showing HOMER slowly backing away into green bushes until he is out of sight",
    "lora_url": "",
    "flow_shift": 9,
    "frame_rate": 24,
    "num_frames": 85,
    "force_offload": true,
    "lora_strength": 1,
    "guidance_scale": 6,
    "denoise_strength": 1
  },
  "logs": "Random seed set to: 3492392950\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 7, title: HunyuanVideo VAE Loader, class type: HyVideoVAELoader\nExecuting node 16, title: (Down)Load HunyuanVideo TextEncoder, class type: DownloadAndLoadHyVideoTextEncoder\n[ComfyUI] Loading text encoder model (clipL) from: /src/ComfyUI/models/clip/clip-vit-large-patch14\n[ComfyUI] Text encoder to dtype: torch.float16\n[ComfyUI] Loading tokenizer (clipL) from: /src/ComfyUI/models/clip/clip-vit-large-patch14\n[ComfyUI] Loading text encoder model (llm) from: /src/ComfyUI/models/LLM/llava-llama-3-8b-text-encoder-tokenizer\n[ComfyUI]\n[ComfyUI] Loading checkpoint shards:   0%|          | 0/4 [00:00<?, ?it/s]\n[ComfyUI] Loading checkpoint shards:  25%|██▌       | 1/4 [00:00<00:01,  1.71it/s]\n[ComfyUI] Loading checkpoint shards:  50%|█████     | 2/4 [00:01<00:01,  1.74it/s]\n[ComfyUI] Loading checkpoint shards:  75%|███████▌  | 3/4 [00:01<00:00,  1.78it/s]\n[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:01<00:00,  2.60it/s]\n[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:01<00:00,  2.21it/s]\n[ComfyUI] Text encoder to dtype: torch.float16\n[ComfyUI] Loading tokenizer (llm) from: /src/ComfyUI/models/LLM/llava-llama-3-8b-text-encoder-tokenizer\nExecuting node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode\n[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 20\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 19\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] Using accelerate to load and assign model weights to device...\n[ComfyUI] Loading LoRA: lora_comfyui with strength: 1.0\n[ComfyUI] Requested to load HyVideoModel\n[ComfyUI] Loading 1 new model\n[ComfyUI] loaded completely 0.0 12555.953247070312 True\n[ComfyUI] Input (height, width, video_length) = (360, 640, 85)\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] Sampling 85 frames in 22 latents at 640x368 with 50 inference steps\n[ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('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<02:09,  2.64s/it]\n[ComfyUI] 4%|▍         | 2/50 [00:06<02:30,  3.13s/it]\n[ComfyUI] 6%|▌         | 3/50 [00:09<02:34,  3.29s/it]\n[ComfyUI] 8%|▊         | 4/50 [00:13<02:34,  3.36s/it]\n[ComfyUI] 10%|█       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3.47s/it]\n[ComfyUI] 80%|████████  | 40/50 [02:17<00:34,  3.46s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [02:21<00:31,  3.46s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [02:24<00:27,  3.46s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [02:28<00:24,  3.46s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [02:31<00:20,  3.46s/it]\n[ComfyUI] 90%|█████████ | 45/50 [02:35<00:17,  3.47s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [02:38<00:13,  3.46s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [02:42<00:10,  3.47s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [02:45<00:06,  3.46s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [02:49<00:03,  3.47s/it]\n[ComfyUI] 100%|██████████| 50/50 [02:52<00:00,  3.47s/it]\n[ComfyUI] 100%|██████████| 50/50 [02:52<00:00,  3.45s/it]\n[ComfyUI] Allocated memory: memory=12.759 GB\n[ComfyUI] Max allocated memory: max_memory=16.810 GB\n[ComfyUI] Max reserved memory: max_reserved=18.688 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,  1.51s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00,  1.26s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00,  1.30s/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, 28.38it/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,  1.18it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:01<00:00,  1.40it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:01<00:00,  1.36it/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, 47.58it/s]\n[ComfyUI] Prompt executed in 207.30 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": 222.619138525,
    "total_time": 250.23631
  },
  "output": "https://replicate.delivery/xezq/PfsvC1StEjQeLkzTsmXsdxKhMMj2enSe6T5rLl32Dgnup4LQB/HunyuanVideo_00001.mp4",
  "started_at": "2025-01-08T07:56:44.486171Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-wsmmv52c2gkjz7mwgcw62keeudnelp4iuyozlxot4p6irsujwczq",
    "get": "https://api.replicate.com/v1/predictions/00pqh8rccnrmc0cm8knb0c69aw",
    "cancel": "https://api.replicate.com/v1/predictions/00pqh8rccnrmc0cm8knb0c69aw/cancel"
  },
  "version": "f0eab4bab4afa1d9d1484a21118bb7539babfac0a119dc41e5b1764a1ec1357b"
}

Generated in

3 minutes 43 seconds

Tweak it ShareReport

Random seed set to: 3492392950
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 7, title: HunyuanVideo VAE Loader, class type: HyVideoVAELoader
Executing node 16, title: (Down)Load HunyuanVideo TextEncoder, class type: DownloadAndLoadHyVideoTextEncoder
[ComfyUI] Loading text encoder model (clipL) from: /src/ComfyUI/models/clip/clip-vit-large-patch14
[ComfyUI] Text encoder to dtype: torch.float16
[ComfyUI] Loading tokenizer (clipL) from: /src/ComfyUI/models/clip/clip-vit-large-patch14
[ComfyUI] Loading text encoder model (llm) from: /src/ComfyUI/models/LLM/llava-llama-3-8b-text-encoder-tokenizer
[ComfyUI]
[ComfyUI] Loading checkpoint shards:   0%|          | 0/4 [00:00<?, ?it/s]
[ComfyUI] Loading checkpoint shards:  25%|██▌       | 1/4 [00:00<00:01,  1.71it/s]
[ComfyUI] Loading checkpoint shards:  50%|█████     | 2/4 [00:01<00:01,  1.74it/s]
[ComfyUI] Loading checkpoint shards:  75%|███████▌  | 3/4 [00:01<00:00,  1.78it/s]
[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:01<00:00,  2.60it/s]
[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:01<00:00,  2.21it/s]
[ComfyUI] Text encoder to dtype: torch.float16
[ComfyUI] Loading tokenizer (llm) from: /src/ComfyUI/models/LLM/llava-llama-3-8b-text-encoder-tokenizer
Executing node 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode
[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 20
[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 19
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] Using accelerate to load and assign model weights to device...
[ComfyUI] Loading LoRA: lora_comfyui with strength: 1.0
[ComfyUI] Requested to load HyVideoModel
[ComfyUI] Loading 1 new model
[ComfyUI] loaded completely 0.0 12555.953247070312 True
[ComfyUI] Input (height, width, video_length) = (360, 640, 85)
Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler
[ComfyUI] Sampling 85 frames in 22 latents at 640x368 with 50 inference steps
[ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('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<02:09,  2.64s/it]
[ComfyUI] 4%|▍         | 2/50 [00:06<02:30,  3.13s/it]
[ComfyUI] 6%|▌         | 3/50 [00:09<02:34,  3.29s/it]
[ComfyUI] 8%|▊         | 4/50 [00:13<02:34,  3.36s/it]
[ComfyUI] 10%|█         | 5/50 [00:16<02:33,  3.41s/it]
[ComfyUI] 12%|█▏        | 6/50 [00:20<02:30,  3.43s/it]
[ComfyUI] 14%|█▍        | 7/50 [00:23<02:28,  3.45s/it]
[ComfyUI] 16%|█▌        | 8/50 [00:26<02:25,  3.45s/it]
[ComfyUI] 18%|█▊        | 9/50 [00:30<02:21,  3.46s/it]
[ComfyUI] 20%|██        | 10/50 [00:33<02:18,  3.46s/it]
[ComfyUI] 22%|██▏       | 11/50 [00:37<02:14,  3.46s/it]
[ComfyUI] 24%|██▍       | 12/50 [00:40<02:11,  3.46s/it]
[ComfyUI] 26%|██▌       | 13/50 [00:44<02:08,  3.46s/it]
[ComfyUI] 28%|██▊       | 14/50 [00:47<02:04,  3.46s/it]
[ComfyUI] 30%|███       | 15/50 [00:51<02:01,  3.46s/it]
[ComfyUI] 32%|███▏      | 16/50 [00:54<01:57,  3.46s/it]
[ComfyUI] 34%|███▍      | 17/50 [00:58<01:54,  3.46s/it]
[ComfyUI] 36%|███▌      | 18/50 [01:01<01:50,  3.46s/it]
[ComfyUI] 38%|███▊      | 19/50 [01:05<01:47,  3.46s/it]
[ComfyUI] 40%|████      | 20/50 [01:08<01:43,  3.46s/it]
[ComfyUI] 42%|████▏     | 21/50 [01:12<01:40,  3.46s/it]
[ComfyUI] 44%|████▍     | 22/50 [01:15<01:37,  3.46s/it]
[ComfyUI] 46%|████▌     | 23/50 [01:18<01:33,  3.46s/it]
[ComfyUI] 48%|████▊     | 24/50 [01:22<01:30,  3.46s/it]
[ComfyUI] 50%|█████     | 25/50 [01:25<01:26,  3.47s/it]
[ComfyUI] 52%|█████▏    | 26/50 [01:29<01:23,  3.46s/it]
[ComfyUI] 54%|█████▍    | 27/50 [01:32<01:19,  3.46s/it]
[ComfyUI] 56%|█████▌    | 28/50 [01:36<01:16,  3.46s/it]
[ComfyUI] 58%|█████▊    | 29/50 [01:39<01:12,  3.47s/it]
[ComfyUI] 60%|██████    | 30/50 [01:43<01:09,  3.46s/it]
[ComfyUI] 62%|██████▏   | 31/50 [01:46<01:05,  3.46s/it]
[ComfyUI] 64%|██████▍   | 32/50 [01:50<01:02,  3.46s/it]
[ComfyUI] 66%|██████▌   | 33/50 [01:53<00:58,  3.47s/it]
[ComfyUI] 68%|██████▊   | 34/50 [01:57<00:55,  3.46s/it]
[ComfyUI] 70%|███████   | 35/50 [02:00<00:51,  3.47s/it]
[ComfyUI] 72%|███████▏  | 36/50 [02:03<00:48,  3.47s/it]
[ComfyUI] 74%|███████▍  | 37/50 [02:07<00:45,  3.47s/it]
[ComfyUI] 76%|███████▌  | 38/50 [02:10<00:41,  3.47s/it]
[ComfyUI] 78%|███████▊  | 39/50 [02:14<00:38,  3.47s/it]
[ComfyUI] 80%|████████  | 40/50 [02:17<00:34,  3.46s/it]
[ComfyUI] 82%|████████▏ | 41/50 [02:21<00:31,  3.46s/it]
[ComfyUI] 84%|████████▍ | 42/50 [02:24<00:27,  3.46s/it]
[ComfyUI] 86%|████████▌ | 43/50 [02:28<00:24,  3.46s/it]
[ComfyUI] 88%|████████▊ | 44/50 [02:31<00:20,  3.46s/it]
[ComfyUI] 90%|█████████ | 45/50 [02:35<00:17,  3.47s/it]
[ComfyUI] 92%|█████████▏| 46/50 [02:38<00:13,  3.46s/it]
[ComfyUI] 94%|█████████▍| 47/50 [02:42<00:10,  3.47s/it]
[ComfyUI] 96%|█████████▌| 48/50 [02:45<00:06,  3.46s/it]
[ComfyUI] 98%|█████████▊| 49/50 [02:49<00:03,  3.47s/it]
[ComfyUI] 100%|██████████| 50/50 [02:52<00:00,  3.47s/it]
[ComfyUI] 100%|██████████| 50/50 [02:52<00:00,  3.45s/it]
[ComfyUI] Allocated memory: memory=12.759 GB
[ComfyUI] Max allocated memory: max_memory=16.810 GB
[ComfyUI] Max reserved memory: max_reserved=18.688 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,  1.51s/it]
[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00,  1.26s/it]
[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00,  1.30s/it]
[ComfyUI]
[ComfyUI] Blending tiles:   0%|          | 0/2 [00:00<?, ?it/s]
[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 28.38it/s]
[ComfyUI]
[ComfyUI] Decoding rows:   0%|          | 0/2 [00:00<?, ?it/s]
[ComfyUI] Decoding rows:  50%|█████     | 1/2 [00:00<00:00,  1.18it/s]
[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:01<00:00,  1.40it/s]
[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:01<00:00,  1.36it/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, 47.58it/s]
[ComfyUI] Prompt executed in 207.30 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.mp4

Examples

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Run time and cost

This model runs on Nvidia H100 GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

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