Prediction
deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9ID
h01kexk0asrm80cmjs3v3cc0e0
Status
Succeeded
Source
API
Hardware
H100
Total duration
Created
Input
- seed
- 12345
- steps
- 50
- width
- 640
- height
- 360
- prompt
- A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace. In the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting. In the distance
- frame_rate
- 16
- num_frames
- 66
- lora_strength
- 1
- guidance_scale
- 6
{
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace.\nIn the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting.\nIn the distance",
"frame_rate": 16,
"num_frames": 66,
"lora_strength": 1,
"guidance_scale": 6
}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 deepfates/hunyuan-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9",
{
input: {
seed: 12345,
steps: 50,
width: 640,
height: 360,
prompt: "A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace.\nIn the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting.\nIn the distance",
frame_rate: 16,
num_frames: 66,
lora_strength: 1,
guidance_scale: 6
}
}
);
// 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-the-matrix-trilogy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"deepfates/hunyuan-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9",
input={
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace.\nIn the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting.\nIn the distance",
"frame_rate": 16,
"num_frames": 66,
"lora_strength": 1,
"guidance_scale": 6
}
)
# 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.
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-the-matrix-trilogy 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-the-matrix-trilogy:e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9",
"input": {
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace.\\nIn the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting.\\nIn the distance",
"frame_rate": 16,
"num_frames": 66,
"lora_strength": 1,
"guidance_scale": 6
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{
"completed_at": "2025-01-24T03:20:26.509237Z",
"created_at": "2025-01-24T03:07:27.702000Z",
"data_removed": false,
"error": null,
"id": "h01kexk0asrm80cmjs3v3cc0e0",
"input": {
"seed": 12345,
"steps": 50,
"width": 640,
"height": 360,
"prompt": "A video in the style of THMTR, THMTR The video clip depicts a horse-drawn carriage traveling along a foggy, winding road. The road is lined with trees on both sides, creating a dense and mysterious atmosphere. The carriage is a traditional style with four large wheels and a roof, pulled by a single horse. The horse is dark in color, possibly black or dark brown, and seems to be moving at a leisurely pace.\nIn the foreground, the road is clearly visible, with rocks and vegetation along the sides. The fog is thick, limiting visibility and adding to the sense of isolation and mystery. The trees are covered in leaves, suggesting a late spring or summer setting.\nIn the distance",
"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\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 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode\n[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 146\n[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77\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]\n[ComfyUI] 0%| | 0/50 [00:00<?, ?it/s]\n[ComfyUI] 2%|▏ | 1/50 [00:02<01:53, 2.31s/it]\n[ComfyUI] 4%|▍ | 2/50 [00:04<01:37, 2.02s/it]\n[ComfyUI] 6%|▌ | 3/50 [00:06<01:41, 2.15s/it]\n[ComfyUI] 8%|▊ | 4/50 [00:08<01:41, 2.21s/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<01:38, 2.28s/it]\n[ComfyUI] 16%|█▌ | 8/50 [00:17<01:36, 2.29s/it]\n[ComfyUI] 18%|█▊ | 9/50 [00:20<01:34, 2.29s/it]\n[ComfyUI] 20%|██ | 10/50 [00:22<01:31, 2.30s/it]\n[ComfyUI] 22%|██▏ | 11/50 [00:24<01:29, 2.30s/it]\n[ComfyUI] 24%|██▍ | 12/50 [00:27<01:27, 2.30s/it]\n[ComfyUI] 26%|██▌ | 13/50 [00:29<01:25, 2.30s/it]\n[ComfyUI] 28%|██▊ | 14/50 [00:31<01:22, 2.30s/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<01:16, 2.30s/it]\n[ComfyUI] 36%|███▌ | 18/50 [00:41<01:13, 2.30s/it]\n[ComfyUI] 38%|███▊ | 19/50 [00:43<01:11, 2.31s/it]\n[ComfyUI] 40%|████ | 20/50 [00:45<01:09, 2.31s/it]\n[ComfyUI] 42%|████▏ | 21/50 [00:47<01:06, 2.31s/it]\n[ComfyUI] 44%|████▍ | 22/50 [00:50<01:04, 2.31s/it]\n[ComfyUI] 46%|████▌ | 23/50 [00:52<01:02, 2.31s/it]\n[ComfyUI] 48%|████▊ | 24/50 [00:54<00:59, 2.31s/it]\n[ComfyUI] 50%|█████ | 25/50 [00:57<00:57, 2.31s/it]\n[ComfyUI] 52%|█████▏ | 26/50 [00:59<00:55, 2.31s/it]\n[ComfyUI] 54%|█████▍ | 27/50 [01:01<00:53, 2.31s/it]\n[ComfyUI] 56%|█████▌ | 28/50 [01:04<00:50, 2.31s/it]\n[ComfyUI] 58%|█████▊ | 29/50 [01:06<00:48, 2.31s/it]\n[ComfyUI] 60%|██████ | 30/50 [01:08<00:46, 2.31s/it]\n[ComfyUI] 62%|██████▏ | 31/50 [01:10<00:43, 2.31s/it]\n[ComfyUI] 64%|██████▍ | 32/50 [01:13<00:41, 2.31s/it]\n[ComfyUI] 66%|██████▌ | 33/50 [01:15<00:39, 2.31s/it]\n[ComfyUI] 68%|██████▊ | 34/50 [01:17<00:36, 2.31s/it]\n[ComfyUI] 70%|███████ | 35/50 [01:20<00:34, 2.31s/it]\n[ComfyUI] 72%|███████▏ | 36/50 [01:22<00:32, 2.31s/it]\n[ComfyUI] 74%|███████▍ | 37/50 [01:24<00:29, 2.31s/it]\n[ComfyUI] 76%|███████▌ | 38/50 [01:27<00:27, 2.31s/it]\n[ComfyUI] 78%|███████▊ | 39/50 [01:29<00:25, 2.31s/it]\n[ComfyUI] 80%|████████ | 40/50 [01:31<00:23, 2.31s/it]\n[ComfyUI] 82%|████████▏ | 41/50 [01:34<00:20, 2.31s/it]\n[ComfyUI] 84%|████████▍ | 42/50 [01:36<00:18, 2.31s/it]\n[ComfyUI] 86%|████████▌ | 43/50 [01:38<00:16, 2.31s/it]\n[ComfyUI] 88%|████████▊ | 44/50 [01:40<00:13, 2.31s/it]\n[ComfyUI] 90%|█████████ | 45/50 [01:43<00:11, 2.31s/it]\n[ComfyUI] 92%|█████████▏| 46/50 [01:45<00:09, 2.31s/it]\n[ComfyUI] 94%|█████████▍| 47/50 [01:47<00:06, 2.31s/it]\n[ComfyUI] 96%|█████████▌| 48/50 [01:50<00:04, 2.31s/it]\n[ComfyUI] 98%|█████████▊| 49/50 [01:52<00:02, 2.31s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.31s/it]\n[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/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=16.281 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, 1.74s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.36s/it]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:02<00:00, 1.42s/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, 25.54it/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, 2.51it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.99it/s]\n[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.91it/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, 64.15it/s]\n[ComfyUI] Prompt executed in 135.73 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": 137.416584363,
"total_time": 778.807237
},
"output": "https://replicate.delivery/xezq/qDLd6D6zyeXLCCAtK9hNeblN3ZF8C2og7NiBLmpeVemqPugQB/HunyuanVideo_00001.mp4",
"started_at": "2025-01-24T03:18:09.092652Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bsvm-jnrsh3yvtuwstvhxj3leseuu3mf64k753kfdjgiuar4hkb73hpna",
"get": "https://api.replicate.com/v1/predictions/h01kexk0asrm80cmjs3v3cc0e0",
"cancel": "https://api.replicate.com/v1/predictions/h01kexk0asrm80cmjs3v3cc0e0/cancel"
},
"version": "e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9"
}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
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 30, title: HunyuanVideo TextEncode, class type: HyVideoTextEncode
[ComfyUI] llm prompt attention_mask shape: torch.Size([1, 161]), masked tokens: 146
[ComfyUI] clipL prompt attention_mask shape: torch.Size([1, 77]), masked tokens: 77
[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]
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[ComfyUI] 100%|██████████| 50/50 [01:54<00:00, 2.30s/it]
[ComfyUI] Allocated memory: memory=12.300 GB
[ComfyUI] Max allocated memory: max_memory=15.099 GB
[ComfyUI] Max reserved memory: max_reserved=16.281 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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[ComfyUI] Decoding rows: 100%|██████████| 2/2 [00:00<00:00, 2.91it/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, 64.15it/s]
[ComfyUI] Prompt executed in 135.73 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'}]}}
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HunyuanVideo_00001.png
HunyuanVideo_00001.mp4