deepfates/hunyuan-the-matrix-trilogy 🔢📝❓✓🖼️ → 🖼️

▶️ 111 runs 📅 Jan 2025 ⚙️ Cog 0.13.6
cinematic-style matrix-style text-to-video video-lora-training

About

Hunyuan-Video model finetuned on The Matrix Trilogy (1999). Trigger word is "THMTR". Use "A video in the style of THMTR, THMTR" at the beginning of your prompt for best results.

Example Output

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"

Output

Performance Metrics

137.42s Prediction Time
778.81s Total Time
All Input Parameters
{
  "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
}
Input Parameters
crf Type: integerDefault: 19Range: 0 - 51
CRF (quality) for H264 encoding. Lower values = higher quality.
seed Type: integer
Set a seed for reproducibility. Random by default.
steps Type: integerDefault: 50Range: 1 - 150
Number of diffusion steps.
width Type: integerDefault: 640Range: 64 - 1536
Width for the generated video.
height Type: integerDefault: 360Range: 64 - 1024
Height for the generated video.
prompt Type: stringDefault:
The text prompt describing your video scene.
lora_url Type: stringDefault:
A URL pointing to your LoRA .safetensors file or a Hugging Face repo (e.g. 'user/repo' - uses the first .safetensors file).
scheduler Default: DPMSolverMultistepScheduler
Algorithm used to generate the video frames.
flow_shift Type: integerDefault: 9Range: 0 - 20
Video continuity factor (flow).
frame_rate Type: integerDefault: 16Range: 1 - 60
Video frame rate.
num_frames Type: integerDefault: 33Range: 1 - 1440
How many frames (duration) in the resulting video.
enhance_end Type: numberDefault: 1Range: 0 - 1
When to end enhancement in the video. Must be greater than enhance_start.
enhance_start Type: numberDefault: 0Range: 0 - 1
When to start enhancement in the video. Must be less than enhance_end.
force_offload Type: booleanDefault: true
Whether to force model layers offloaded to CPU.
lora_strength Type: numberDefault: 1Range: -10 - 10
Scale/strength for your LoRA.
enhance_double Type: booleanDefault: true
Apply enhancement across frame pairs.
enhance_single Type: booleanDefault: true
Apply enhancement to individual frames.
enhance_weight Type: numberDefault: 0.3Range: 0 - 2
Strength of the video enhancement effect.
guidance_scale Type: numberDefault: 6Range: 0 - 30
Overall influence of text vs. model.
denoise_strength Type: numberDefault: 1Range: 0 - 2
Controls how strongly noise is applied each step.
replicate_weights Type: string
A .tar file containing LoRA weights from replicate.
Output Schema

Output

Type: stringFormat: uri

Example Execution Logs
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
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[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
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Executing node 34, title: Video Combine 🎥🅥🅗🅢, class type: VHS_VideoCombine
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[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'}]}}
====================================
HunyuanVideo_00001.png
HunyuanVideo_00001.mp4
Version Details
Version ID
e84c3dd23de21d8696fc4961b3960862a7efaf868393382119dab5a11acb0ad9
Version Created
January 23, 2025
Run on Replicate →