ComfyUI_Wan2_1_lora_trainer

By jaimitoesView on GitHub →

Musubi Tuner by kohya_ss

How much VRAM does ComfyUI_Wan2_1_lora_trainer require?

Direct Answer: The ComfyUI node ComfyUI_Wan2_1_lora_trainer requires a minimum base VRAM of 128MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.

High (2-4GB)
Base VRAM:
128MB (0.1GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
MEDIUM

Interactive VRAM Compatibility Estimator

Estimated Total VRAM: 3.00 GBTarget: 8 GB
✅ Comfortable Fit

Your GPU has plenty of headroom. You can run this node safely with your active configurations!

Deploy on High-Performance GPUs

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🚀 Deploy on Vast.ai

Deploy on Cloud GPUs

Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance cloud GPUs on RunPod instantly.

🚀 Deploy on RunPod

What Python packages are required for ComfyUI_Wan2_1_lora_trainer?

Direct Answer: Running ComfyUI_Wan2_1_lora_trainer requires installing the following Python package dependencies: accelerate>=1.6.0, av>=14.0.1, bitsandbytes>=0.45.4, diffusers>=0.32.1, easydict>=1.13, einops>=0.7.0, ftfy>=6.3.1, huggingface-hub>=0.30.0, opencv-python>=4.10.0.84, pillow, safetensors>=0.4.5, tensorboard, toml>=0.10.2, tqdm>=4.67.1, transformers>=4.46.3, voluptuous>=0.15.2, wandb. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
accelerate>=1.6.0
av>=14.0.1
bitsandbytes>=0.45.4
diffusers>=0.32.1
easydict>=1.13
einops>=0.7.0
ftfy>=6.3.1
huggingface-hub>=0.30.0
opencv-python>=4.10.0.84
pillow
safetensors>=0.4.5
tensorboard
toml>=0.10.2
tqdm>=4.67.1
transformers>=4.46.3
voluptuous>=0.15.2
wandb

Interactive Setup & Dependency Resolver

Operating System:
Environment Type:
Run this terminal command in your ComfyUI root folder:
# Loading command...

Frequently Asked Questions

How much VRAM does ComfyUI_Wan2_1_lora_trainer require?

ComfyUI_Wan2_1_lora_trainer requires a minimum of 128MB (0.1GB) of VRAM for base operation. For optimal performance, a GPU with at least 4GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.

Can I run ComfyUI_Wan2_1_lora_trainer on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.3GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.5GB headroom

What Python packages are required for ComfyUI_Wan2_1_lora_trainer?

To run ComfyUI_Wan2_1_lora_trainer, you need to install: accelerate>=1.6.0, av>=14.0.1, bitsandbytes>=0.45.4, diffusers>=0.32.1, easydict>=1.13, einops>=0.7.0, ftfy>=6.3.1, huggingface-hub>=0.30.0, opencv-python>=4.10.0.84, pillow, safetensors>=0.4.5, tensorboard, toml>=0.10.2, tqdm>=4.67.1, transformers>=4.46.3, voluptuous>=0.15.2, wandb. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI_Wan2_1_lora_trainer?

ComfyUI_Wan2_1_lora_trainer supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.

How do I install ComfyUI_Wan2_1_lora_trainer in ComfyUI?

To install ComfyUI_Wan2_1_lora_trainer: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/jaimitoes/ComfyUI_Wan2_1_lora_trainer, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.