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deepfates / hunyuan-once-upon-a-time-in-hollywood
Hunyuan-Video model finetuned on Once Upon a Time in Hollywood (2019). Trigger word is "NCPNT". Use "A video in the style of NCPNT, NCPNT" at the beginning of your prompt for best results.
- Public
- 72 runs
-
H100
- Fine-tune
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=deepfates/hunyuan-once-upon-a-time-in-hollywood
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet 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 deepfates/hunyuan-once-upon-a-time-in-hollywood using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"deepfates/hunyuan-once-upon-a-time-in-hollywood:47e048cf3de47305fccb9410f2d9c9f89e626a38e1d6dc08561698c5d8ffa2b3",
{
input: {
crf: 19,
seed: 12345,
steps: 50,
width: 640,
height: 360,
prompt: "A video in the style of NCPNT, NCPNT The video clip depicts a dimly lit jazz club with a cozy, intimate atmosphere. The stage is set with a piano and a saxophone player, both engrossed in their performance. The saxophonist is positioned in the center, playing with a focused expression, while the pianist sits at the back, immersed in his music. The club is filled with patrons seated at tables, engaged in conversation and enjoying the live music. The audience appears to be a mix of men and women, dressed in casual to semi-formal attire. The lighting is warm and subdued, with a neon sign on the right side of the stage reading ",
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 replicateSet 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 replicateRun deepfates/hunyuan-once-upon-a-time-in-hollywood using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"deepfates/hunyuan-once-upon-a-time-in-hollywood:47e048cf3de47305fccb9410f2d9c9f89e626a38e1d6dc08561698c5d8ffa2b3",
input={
"crf": 19,
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of NCPNT, NCPNT The video clip depicts a dimly lit jazz club with a cozy, intimate atmosphere. The stage is set with a piano and a saxophone player, both engrossed in their performance. The saxophonist is positioned in the center, playing with a focused expression, while the pianist sits at the back, immersed in his music. The club is filled with patrons seated at tables, engaged in conversation and enjoying the live music. The audience appears to be a mix of men and women, dressed in casual to semi-formal attire. The lighting is warm and subdued, with a neon sign on the right side of the stage reading ",
"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-once-upon-a-time-in-hollywood 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-once-upon-a-time-in-hollywood:47e048cf3de47305fccb9410f2d9c9f89e626a38e1d6dc08561698c5d8ffa2b3",
"input": {
"crf": 19,
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of NCPNT, NCPNT The video clip depicts a dimly lit jazz club with a cozy, intimate atmosphere. The stage is set with a piano and a saxophone player, both engrossed in their performance. The saxophonist is positioned in the center, playing with a focused expression, while the pianist sits at the back, immersed in his music. The club is filled with patrons seated at tables, engaged in conversation and enjoying the live music. The audience appears to be a mix of men and women, dressed in casual to semi-formal attire. The lighting is warm and subdued, with a neon sign on the right side of the stage reading ",
"lora_url": "",
"scheduler": "DPMSolverMultistepScheduler",
"flow_shift": 9,
"frame_rate": 16,
"num_frames": 66,
"enhance_end": 1,
"enhance_start": 0,
"force_offload": true,
"lora_strength": 1,
"enhance_double": true,
"enhance_single": true,
"enhance_weight": 0.3,
"guidance_scale": 6,
"denoise_strength": 1
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:
brew install cogIf 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-once-upon-a-time-in-hollywood@sha256:47e048cf3de47305fccb9410f2d9c9f89e626a38e1d6dc08561698c5d8ffa2b3 \
-i 'crf=19' \
-i 'seed=12345' \
-i 'steps=50' \
-i 'width=640' \
-i 'height=360' \
-i 'prompt="A video in the style of NCPNT, NCPNT The video clip depicts a dimly lit jazz club with a cozy, intimate atmosphere. The stage is set with a piano and a saxophone player, both engrossed in their performance. The saxophonist is positioned in the center, playing with a focused expression, while the pianist sits at the back, immersed in his music. The club is filled with patrons seated at tables, engaged in conversation and enjoying the live music. The audience appears to be a mix of men and women, dressed in casual to semi-formal attire. The lighting is warm and subdued, with a neon sign on the right side of the stage reading "' \
-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-once-upon-a-time-in-hollywood@sha256:47e048cf3de47305fccb9410f2d9c9f89e626a38e1d6dc08561698c5d8ffa2b3curl -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 NCPNT, NCPNT The video clip depicts a dimly lit jazz club with a cozy, intimate atmosphere. The stage is set with a piano and a saxophone player, both engrossed in their performance. The saxophonist is positioned in the center, playing with a focused expression, while the pianist sits at the back, immersed in his music. The club is filled with patrons seated at tables, engaged in conversation and enjoying the live music. The audience appears to be a mix of men and women, dressed in casual to semi-formal attire. The lighting is warm and subdued, with a neon sign on the right side of the stage reading ", "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.
Sign in with GitHub
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terms of service and privacy policy
Output
{
"completed_at": "2025-01-24T18:52:27.357534Z",
"created_at": "2025-01-24T18:47:17.213000Z",
"data_removed": false,
"error": null,
"id": "nrwdpg6fvnrme0cmk6hrkgddm4",
"input": {
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of NCPNT, NCPNT The video clip depicts a dimly lit jazz club with a cozy, intimate atmosphere. The stage is set with a piano and a saxophone player, both engrossed in their performance. The saxophonist is positioned in the center, playing with a focused expression, while the pianist sits at the back, immersed in his music. The club is filled with patrons seated at tables, engaged in conversation and enjoying the live music. The audience appears to be a mix of men and women, dressed in casual to semi-formal attire. The lighting is warm and subdued, with a neon sign on the right side of the stage reading ",
"frame_rate": 16,
"num_frames": 66,
"lora_strength": 1,
"guidance_scale": 6
},
"logs": "Seed set to: 12345\n⚠️ Adjusted dimensions from 640x360 to 640x368 to satisfy model requirements\n⚠️ Adjusted frame count from 66 to 65 to satisfy model requirements\n�� USING REPLICATE WEIGHTS (preferred method)\n🎯 USING REPLICATE WEIGHTS TAR FILE 🎯\n----------------------------------------\n📦 Processing replicate weights tar file...\n🔄 Will rename LoRA to: replicate_9fda3c62-41dc-43bf-adeb-1d83016c8c1d.safetensors\n📂 Extracting tar contents...\n✅ Found lora_comfyui.safetensors in tar\n✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_9fda3c62-41dc-43bf-adeb-1d83016c8c1d.safetensors\n----------------------------------------\nChecking inputs\n====================================\nChecking weights\n✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models\n✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae\n====================================\nRunning workflow\n[ComfyUI] got prompt\nExecuting node 7, title: HunyuanVideo VAE Loader, class type: HyVideoVAELoader\nExecuting node 42, title: HunyuanVideo Enhance A Video, class type: HyVideoEnhanceAVideo\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<00:02, 1.15it/s]\n[ComfyUI] Loading checkpoint shards: 50%|█████ | 2/4 [00:01<00:01, 1.20it/s]\n[ComfyUI] Loading checkpoint shards: 75%|███████▌ | 3/4 [00:02<00:00, 1.33it/s]\n[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:02<00:00, 1.99it/s]\n[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:02<00:00, 1.63it/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: 142\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77\nExecuting node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect\nExecuting node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader\n[ComfyUI] model_type FLOW\n[ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Using accelerate to load and assign model weights to device...\n[ComfyUI] Loading LoRA: replicate_9fda3c62-41dc-43bf-adeb-1d83016c8c1d with strength: 1.0\n[ComfyUI] Requested to load HyVideoModel\n[ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True\n[ComfyUI] Input (height, width, video_length) = (368, 640, 65)\nExecuting node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler\n[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n[ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps\n[ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['num_train_timesteps', 'n_tokens'])])\n[ComfyUI]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:58, 2.43s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:39, 2.07s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:42, 2.18s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:42, 2.22s/it]\n[ComfyUI] 10%|█ | 5/50 [00:11<01:41, 2.25s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:13<01:39, 2.27s/it]\n[ComfyUI] 14%|█▍ | 7/50 [00:15<01:37, 2.28s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:18<01:35, 2.28s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:33, 2.29s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.29s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.29s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.29s/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, 2.30s/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 [00:57<00:57, 2.30s/it]\n[ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.30s/it]\n[ComfyUI] 54%|█████▍ | 27/50 [01:01<00:52, 2.30s/it]\n[ComfyUI] 56%|█████▌ | 28/50 [01:03<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 [01:20<00:34, 2.30s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.30s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.30s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:26<00:27, 2.30s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.30s/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 [01:43<00:11, 2.30s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.30s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.30s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:49<00:04, 2.30s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.29s/it]\n[ComfyUI] Allocated memory: memory=12.760 GB\n[ComfyUI] Max allocated memory: max_memory=15.559 GB\n[ComfyUI] Max reserved memory: max_reserved=16.875 GB\n[ComfyUI]\nExecuting node 5, title: HunyuanVideo Decode, class type: HyVideoDecode\n[ComfyUI] Decoding rows: 0%| | 0/2 [00:00<?, ?it/s]\n[ComfyUI] Decoding rows: 50%|█████ | 1/2 [00:01<00:01, 1.50s/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, 1.29s/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, 28.50it/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, 2.48it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.94it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.85it/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, 39.06it/s]\n[ComfyUI] Prompt executed in 152.18 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": 157.124447691,
"total_time": 310.144534
},
"output": "https://replicate.delivery/xezq/eVeK5uDOzlvKwU0kfISce9CAfX9R3pfp62bhL7SjVUi0aTGCF/HunyuanVideo_00001.mp4",
"started_at": "2025-01-24T18:49:50.233087Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bsvm-og7cajjyof5q22n2iiukghsuz4moebhxaydb3rxhn5gjatusfspq",
"get": "https://api.replicate.com/v1/predictions/nrwdpg6fvnrme0cmk6hrkgddm4",
"cancel": "https://api.replicate.com/v1/predictions/nrwdpg6fvnrme0cmk6hrkgddm4/cancel"
},
"version": "47e048cf3de47305fccb9410f2d9c9f89e626a38e1d6dc08561698c5d8ffa2b3"
}Generated in
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
�� USING REPLICATE WEIGHTS (preferred method)
🎯 USING REPLICATE WEIGHTS TAR FILE 🎯
----------------------------------------
📦 Processing replicate weights tar file...
🔄 Will rename LoRA to: replicate_9fda3c62-41dc-43bf-adeb-1d83016c8c1d.safetensors
📂 Extracting tar contents...
✅ Found lora_comfyui.safetensors in tar
✨ Successfully copied LoRA to: ComfyUI/models/loras/replicate_9fda3c62-41dc-43bf-adeb-1d83016c8c1d.safetensors
----------------------------------------
Checking inputs
====================================
Checking weights
✅ hunyuan_video_720_fp8_e4m3fn.safetensors exists in ComfyUI/models/diffusion_models
✅ hunyuan_video_vae_bf16.safetensors exists in ComfyUI/models/vae
====================================
Running workflow
[ComfyUI] got prompt
Executing node 7, title: HunyuanVideo VAE Loader, class type: HyVideoVAELoader
Executing node 42, title: HunyuanVideo Enhance A Video, class type: HyVideoEnhanceAVideo
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<00:02, 1.15it/s]
[ComfyUI] Loading checkpoint shards: 50%|█████ | 2/4 [00:01<00:01, 1.20it/s]
[ComfyUI] Loading checkpoint shards: 75%|███████▌ | 3/4 [00:02<00:00, 1.33it/s]
[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:02<00:00, 1.99it/s]
[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:02<00:00, 1.63it/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: 142
[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77
Executing node 41, title: HunyuanVideo Lora Select, class type: HyVideoLoraSelect
Executing node 1, title: HunyuanVideo Model Loader, class type: HyVideoModelLoader
[ComfyUI] model_type FLOW
[ComfyUI] The config attributes {'use_flow_sigmas': True, 'prediction_type': 'flow_prediction'} were passed to FlowMatchDiscreteScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.
[ComfyUI] Using accelerate to load and assign model weights to device...
[ComfyUI] Loading LoRA: replicate_9fda3c62-41dc-43bf-adeb-1d83016c8c1d with strength: 1.0
[ComfyUI] Requested to load HyVideoModel
[ComfyUI] loaded completely 9.5367431640625e+25 12555.953247070312 True
[ComfyUI] Input (height, width, video_length) = (368, 640, 65)
Executing node 3, title: HunyuanVideo Sampler, class type: HyVideoSampler
[ComfyUI] The config attributes {'reverse': True, 'solver': 'euler'} were passed to DPMSolverMultistepScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.
[ComfyUI] Sampling 65 frames in 17 latents at 640x368 with 50 inference steps
[ComfyUI] Scheduler config: FrozenDict([('num_train_timesteps', 1000), ('flow_shift', 9.0), ('reverse', True), ('solver', 'euler'), ('n_tokens', None), ('_use_default_values', ['num_train_timesteps', 'n_tokens'])])
[ComfyUI]
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[ComfyUI] Allocated memory: memory=12.760 GB
[ComfyUI] Max allocated memory: max_memory=15.559 GB
[ComfyUI] Max reserved memory: max_reserved=16.875 GB
[ComfyUI]
Executing node 5, title: HunyuanVideo Decode, class type: HyVideoDecode
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[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, 39.06it/s]
[ComfyUI] Prompt executed in 152.18 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.mp4Examples
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.
