ComfyUI Neural Network Toolkit NNT

By inventoradoView on GitHub →

Neural Network Toolkit (NNT) for ComfyUI is an extensive set of custom ComfyUI nodes for designing, training, and fine-tuning neural networks. This toolkit allows defining models, layers, training workflows, transformers, and tensor operations in a visual manner using nodes.

How much VRAM does ComfyUI Neural Network Toolkit NNT require?

Direct Answer: The ComfyUI node ComfyUI Neural Network Toolkit NNT requires a minimum base VRAM of 256MB 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:
256MB (0.3GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
HIGH

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!

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What Python packages are required for ComfyUI Neural Network Toolkit NNT ?

Direct Answer: Running ComfyUI Neural Network Toolkit NNT requires installing the following Python package dependencies: cloudpickle>=2.2.0 # Required for shap, datasets>=2.12.0, graphviz>=0.20.0, h5py>=3.7.0, huggingface-hub>=0.16.0, joblib>=1.1.0, librosa>=0.10.0, matplotlib>=3.4.0, numba>=0.55.1 # Required for shap, numpy>=1.21.0, onnx>=1.14.0, pandas>=1.3.0, pillow>=9.0.0, protobuf>=3.20.0 # Required for onnx, safetensors>=0.3.1, scikit-learn>=1.0.0, scipy>=1.7.0, seaborn>=0.11.0, shap==0.41.0, slicer>=0.0.7 # Required for shap, statsmodels>=0.13.0, torch>=2.0.0, torchview>=0.2.0, torchvision>=0.15.0, tqdm>=4.65.0 # Progress bars, transformers>=4.30.0. This node specifically requires PyTorch version 2.0.0 or newer.

requirements.txt
cloudpickle>=2.2.0  # Required for shap
datasets>=2.12.0
graphviz>=0.20.0
h5py>=3.7.0
huggingface-hub>=0.16.0
joblib>=1.1.0
librosa>=0.10.0
matplotlib>=3.4.0
numba>=0.55.1  # Required for shap
numpy>=1.21.0
onnx>=1.14.0
pandas>=1.3.0
pillow>=9.0.0
protobuf>=3.20.0  # Required for onnx
safetensors>=0.3.1
scikit-learn>=1.0.0
scipy>=1.7.0
seaborn>=0.11.0
shap==0.41.0
slicer>=0.0.7  # Required for shap
statsmodels>=0.13.0
torch>=2.0.0
torchview>=0.2.0
torchvision>=0.15.0
tqdm>=4.65.0  # Progress bars
transformers>=4.30.0

Interactive Setup & Dependency Resolver

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

Special Environment Requirements:

Requires PyTorch version 2.0.0+.

To update PyTorch for your selected setup, run:
# Loading PyTorch command...

Related Custom Nodes

The following custom nodes run in the same PyTorch / CUDA environment and share similar categories or workflows:

ComfyUI DMOSpeech2 Node
by HM-RunningHub128MB VRAM
ComfyUI Zonos TTS Node
by BahaC256MB VRAM
ComfyUI-Geeky-Kokoro-TTS
by GeekyGhost1.5GB VRAM
ComfyUI_FL-SongGen
by filliptm128MB VRAM
FL Voxtral TTS
by filliptm128MB VRAM

Frequently Asked Questions

How much VRAM does ComfyUI Neural Network Toolkit NNT require?

ComfyUI Neural Network Toolkit NNT requires a minimum of 256MB (0.3GB) 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 Neural Network Toolkit NNT on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.2GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.4GB headroom

What PyTorch version does ComfyUI Neural Network Toolkit NNT need?

ComfyUI Neural Network Toolkit NNT requires the following PyTorch-related packages: torch>=2.0.0, torchview>=0.2.0, torchvision>=0.15.0. Ensure your ComfyUI environment has these installed. Ensure your PyTorch installation matches your CUDA version (use torch.version.cuda to check).

What Python packages are required for ComfyUI Neural Network Toolkit NNT ?

To run ComfyUI Neural Network Toolkit NNT , you need to install: cloudpickle>=2.2.0 # Required for shap, datasets>=2.12.0, graphviz>=0.20.0, h5py>=3.7.0, huggingface-hub>=0.16.0, joblib>=1.1.0, librosa>=0.10.0, matplotlib>=3.4.0, numba>=0.55.1 # Required for shap, numpy>=1.21.0, onnx>=1.14.0, pandas>=1.3.0, pillow>=9.0.0, protobuf>=3.20.0 # Required for onnx, safetensors>=0.3.1, scikit-learn>=1.0.0, scipy>=1.7.0, seaborn>=0.11.0, shap==0.41.0, slicer>=0.0.7 # Required for shap, statsmodels>=0.13.0, torch>=2.0.0, torchview>=0.2.0, torchvision>=0.15.0, tqdm>=4.65.0 # Progress bars, transformers>=4.30.0. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI Neural Network Toolkit NNT ?

ComfyUI Neural Network Toolkit NNT 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 Neural Network Toolkit NNT in ComfyUI?

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