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fofr / hunyuan-take-on-me
Hunyuan fine-tuned on 3s clips from A-ha's Take on Me music video, use TKONME trigger
- Public
- 64 runs
-
H100
- Fine-tune
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=fofr/hunyuan-take-on-me
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";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run fofr/hunyuan-take-on-me using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"fofr/hunyuan-take-on-me:fe4347d905314abbcb3270b1abd5aa370dff6d61d769b59ea8a91961c40ba420",
{
input: {
crf: 19,
steps: 50,
width: 640,
height: 360,
prompt: "In the style of TKONME, this video sequence is a sketched animations depicting a young woman with hair in a bun and loose strands, she looks up.",
lora_url: "",
scheduler: "DPMSolverMultistepScheduler",
flow_shift: 9,
frame_rate: 24,
num_frames: 85,
enhance_end: 1,
enhance_start: 0,
force_offload: true,
lora_strength: 0.85,
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 fofr/hunyuan-take-on-me using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"fofr/hunyuan-take-on-me:fe4347d905314abbcb3270b1abd5aa370dff6d61d769b59ea8a91961c40ba420",
input={
"crf": 19,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "In the style of TKONME, this video sequence is a sketched animations depicting a young woman with hair in a bun and loose strands, she looks up.",
"lora_url": "",
"scheduler": "DPMSolverMultistepScheduler",
"flow_shift": 9,
"frame_rate": 24,
"num_frames": 85,
"enhance_end": 1,
"enhance_start": 0,
"force_offload": True,
"lora_strength": 0.85,
"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-take-on-me 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": "fofr/hunyuan-take-on-me:fe4347d905314abbcb3270b1abd5aa370dff6d61d769b59ea8a91961c40ba420",
"input": {
"crf": 19,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "In the style of TKONME, this video sequence is a sketched animations depicting a young woman with hair in a bun and loose strands, she looks up.",
"lora_url": "",
"scheduler": "DPMSolverMultistepScheduler",
"flow_shift": 9,
"frame_rate": 24,
"num_frames": 85,
"enhance_end": 1,
"enhance_start": 0,
"force_offload": true,
"lora_strength": 0.85,
"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/fofr/hunyuan-take-on-me@sha256:fe4347d905314abbcb3270b1abd5aa370dff6d61d769b59ea8a91961c40ba420 \
-i 'crf=19' \
-i 'steps=50' \
-i 'width=640' \
-i 'height=360' \
-i 'prompt="In the style of TKONME, this video sequence is a sketched animations depicting a young woman with hair in a bun and loose strands, she looks up."' \
-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=0.85' \
-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-take-on-me@sha256:fe4347d905314abbcb3270b1abd5aa370dff6d61d769b59ea8a91961c40ba420curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "crf": 19, "steps": 50, "width": 640, "height": 360, "prompt": "In the style of TKONME, this video sequence is a sketched animations depicting a young woman with hair in a bun and loose strands, she looks up.", "lora_url": "", "scheduler": "DPMSolverMultistepScheduler", "flow_shift": 9, "frame_rate": 24, "num_frames": 85, "enhance_end": 1, "enhance_start": 0, "force_offload": true, "lora_strength": 0.85, "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
By signing in, you agree to our
terms of service and privacy policy
Output
{
"completed_at": "2025-01-09T00:15:56.045993Z",
"created_at": "2025-01-09T00:11:27.911000Z",
"data_removed": false,
"error": null,
"id": "bgechwpv4xrme0cm91kaz29vqw",
"input": {
"crf": 19,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "In the style of TKONME, this video sequence is a sketched animations depicting a young woman with hair in a bun and loose strands, she looks up.",
"lora_url": "",
"flow_shift": 9,
"frame_rate": 24,
"num_frames": 85,
"force_offload": true,
"lora_strength": 0.85,
"guidance_scale": 6,
"denoise_strength": 1
},
"logs": "Random seed set to: 171269911\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 7, title: HunyuanVideo VAE Loader, class type: HyVideoVAELoader\n[ComfyUI] Loading text encoder model (clipL) from: /src/ComfyUI/models/clip/clip-vit-large-patch14\nExecuting node 16, title: (Down)Load HunyuanVideo TextEncoder, class type: DownloadAndLoadHyVideoTextEncoder\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, 1.58it/s]\n[ComfyUI] Loading checkpoint shards: 50%|█████ | 2/4 [00:01<00:01, 1.63it/s]\n[ComfyUI] Loading checkpoint shards: 75%|███████▌ | 3/4 [00:01<00:00, 1.66it/s]\n[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:01<00:00, 2.38it/s]\n[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:01<00:00, 2.04it/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: 34\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 35\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: 0.85\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, 3.28s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:13<02:34, 3.36s/it]\n[ComfyUI] 10%|█ | 5/50 [00:16<02:32, 3.40s/it]\n[ComfyUI] 12%|█▏ | 6/50 [00:19<02:30, 3.42s/it]\n[ComfyUI] 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[02:31<00:20, 3.47s/it]\n[ComfyUI] 90%|█████████ | 45/50 [02:35<00:17, 3.47s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [02:38<00:13, 3.47s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [02:42<00:10, 3.47s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [02:45<00:06, 3.47s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [02:49<00:03, 3.48s/it]\n[ComfyUI] 100%|██████████| 50/50 [02:52<00:00, 3.47s/it]\n[ComfyUI] 100%|██████████| 50/50 [02:52<00:00, 3.46s/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, 1.52s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.27s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.31s/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, 28.42it/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, 1.39it/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, 49.09it/s]\n[ComfyUI] Prompt executed in 208.11 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": 212.95651648,
"total_time": 268.134993
},
"output": "https://replicate.delivery/xezq/4MZJp0bfMmQzYysOOyCssH1U4UrGoPtWl08dFJLYe1F8cMDUA/HunyuanVideo_00001.mp4",
"started_at": "2025-01-09T00:12:23.089477Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-zf5bfjbqopp3pudrrjzcdpr62gt5kmyhh2fzeroisnrjy5sxxujq",
"get": "https://api.replicate.com/v1/predictions/bgechwpv4xrme0cm91kaz29vqw",
"cancel": "https://api.replicate.com/v1/predictions/bgechwpv4xrme0cm91kaz29vqw/cancel"
},
"version": "fe4347d905314abbcb3270b1abd5aa370dff6d61d769b59ea8a91961c40ba420"
}Generated in
Random seed set to: 171269911
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 7, title: HunyuanVideo VAE Loader, class type: HyVideoVAELoader
[ComfyUI] Loading text encoder model (clipL) from: /src/ComfyUI/models/clip/clip-vit-large-patch14
Executing node 16, title: (Down)Load HunyuanVideo TextEncoder, class type: DownloadAndLoadHyVideoTextEncoder
[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]
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[ComfyUI] Loading checkpoint shards: 100%|██████████| 4/4 [00:01<00:00, 2.04it/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: 34
[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 35
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: 0.85
[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]
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[ComfyUI] 56%|█████▌ | 28/50 [01:36<01:16, 3.47s/it]
[ComfyUI] 58%|█████▊ | 29/50 [01:39<01:12, 3.47s/it]
[ComfyUI] 60%|██████ | 30/50 [01:43<01:09, 3.47s/it]
[ComfyUI] 62%|██████▏ | 31/50 [01:46<01:06, 3.47s/it]
[ComfyUI] 64%|██████▍ | 32/50 [01:50<01:02, 3.47s/it]
[ComfyUI] 66%|██████▌ | 33/50 [01:53<00:59, 3.47s/it]
[ComfyUI] 68%|██████▊ | 34/50 [01:57<00:55, 3.47s/it]
[ComfyUI] 70%|███████ | 35/50 [02:00<00:52, 3.47s/it]
[ComfyUI] 72%|███████▏ | 36/50 [02:04<00:48, 3.47s/it]
[ComfyUI] 74%|███████▍ | 37/50 [02:07<00:45, 3.47s/it]
[ComfyUI] 76%|███████▌ | 38/50 [02:11<00:41, 3.47s/it]
[ComfyUI] 78%|███████▊ | 39/50 [02:14<00:38, 3.47s/it]
[ComfyUI] 80%|████████ | 40/50 [02:18<00:34, 3.47s/it]
[ComfyUI] 82%|████████▏ | 41/50 [02:21<00:31, 3.47s/it]
[ComfyUI] 84%|████████▍ | 42/50 [02:25<00:27, 3.47s/it]
[ComfyUI] 86%|████████▌ | 43/50 [02:28<00:24, 3.47s/it]
[ComfyUI] 88%|████████▊ | 44/50 [02:31<00:20, 3.47s/it]
[ComfyUI] 90%|█████████ | 45/50 [02:35<00:17, 3.47s/it]
[ComfyUI] 92%|█████████▏| 46/50 [02:38<00:13, 3.47s/it]
[ComfyUI] 94%|█████████▍| 47/50 [02:42<00:10, 3.47s/it]
[ComfyUI] 96%|█████████▌| 48/50 [02:45<00:06, 3.47s/it]
[ComfyUI] 98%|█████████▊| 49/50 [02:49<00:03, 3.48s/it]
[ComfyUI] 100%|██████████| 50/50 [02:52<00:00, 3.47s/it]
[ComfyUI] 100%|██████████| 50/50 [02:52<00:00, 3.46s/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, 1.52s/it]
[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.27s/it]
[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.31s/it]
[ComfyUI]
[ComfyUI] Blending tiles: 0%| | 0/2 [00:00<?, ?it/s]
[ComfyUI] Blending tiles: 100%|██████████| 2/2 [00:00<00:00, 28.42it/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, 1.39it/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, 49.09it/s]
[ComfyUI] Prompt executed in 208.11 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.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.
