ComfyUI-WorkflowGenerator Models
This repository contains the quantized GGUF models required for
ComfyUI-WorkflowGenerator , a custom node implementation that generates ComfyUI workflows from natural language descriptions.
Models Included
1. Workflow Generator Model (Required)
File : workflow-generator-q8_0.gguf
Tokenizer : workflow-generator/ directory
Purpose : Generates workflow diagrams from natural language instructions
Base Model : Qwen2.5-14B
Training : Fine-tuned from Qwen2.5-14B using LLaMA-Factory (see original ComfyGPT repository )
Status : Required - This model is always needed
2. Embedding Model (Required)
Directory : paraphrase-multilingual-MiniLM-L12-v2/
Purpose : Semantic search for node name matching and validation
Base Model : sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
Status : Required - Always needed for semantic search in NodeValidator
3. Node Validator Model (Optional)
File : Qwen2.5-7B-Instruct-q8_0.gguf
Tokenizer : Qwen2.5-7B-Instruct/ directory
Purpose : Refines and corrects node names in workflow diagrams (LLM refinement mode)
Base Model : Qwen2.5-7B-Instruct (base model, not fine-tuned)
Status : Optional - Only needed if using LLM refinement (use_llm_refinement=True)
Model Training Information
Workflow Generator Model
The
workflow-generator-q8_0.gguf model was trained based on the
ComfyGPT research methodology:
Original Model Source : xiatianzs/resources - Original fine-tuned model from ComfyGPT research team
Base Model : Qwen/Qwen2.5-14B from HuggingFace
Training Method : Full fine-tuning (Supervised Fine-Tuning / SFT)
Training Framework : LLaMA-Factory
Training Dataset : FlowDataset.json - Contains instruction-input-output pairs where:
Instruction: "Based on the description I provided, generate a JSON example of the required ComfyUi workflow."
Input: Natural language workflow descriptions
Output: JSON diagrams (list of edges representing workflow connections)
Training Hyperparameters :
Learning rate: 1.0e-5
Epochs: 3.0
Batch size: 1 per device (gradient accumulation: 4 steps)
LR scheduler: Cosine with 0.1 warmup ratio
Precision: bf16
Cutoff length: 8,192 tokens (training cutoff; model architecture supports up to 131,072 tokens)
DeepSpeed: ZeRO-3 optimization
Quantization : q8_0 (8-bit quantization for efficient inference)
For more details on the training process, see the
original ComfyGPT repository and
training configuration .
Embedding Model
The paraphrase-multilingual-MiniLM-L12-v2 model is a SentenceTransformer model used for semantic search in the NodeValidator. It encodes node names into embeddings and finds the most similar nodes when correcting invalid node names in workflow diagrams.
Original Model : sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
Type : SentenceTransformer (HuggingFace format)
Size : ~420 MB
Dimensions : 384 (embedding vector size)
Use Case : Semantic similarity search for node name matching
Node Validator Model
The
Qwen2.5-7B-Instruct-q8_0.gguf model is the base
Qwen2.5-7B-Instruct model (not fine-tuned), used for its built-in instruction-following capabilities to select the best node from semantic search candidates.
Quick Download
Download all models at once:
1 huggingface-cli download DanielPFlorian/comfyui-workflowgenerator-models \
2 --local-dir ./ComfyUI/models/LLM/
Or download specific models:
1 # Download only the required models (workflow-generator + embedding model)
2 huggingface-cli download DanielPFlorian/comfyui-workflowgenerator-models \
3 --include "workflow-generator-q8_0.gguf" "workflow-generator/*" "paraphrase-multilingual-MiniLM-L12-v2/*" \
4 --local-dir ./ComfyUI/models/LLM/
Installation and Setup
Step 1: Download Models
Download the models to your ComfyUI models directory:
1 # Navigate to ComfyUI directory
2 cd /path/to/ComfyUI
3
4 # Download all models
5 huggingface-cli download DanielPFlorian/comfyui-workflowgenerator-models \
6 --local-dir ./models/LLM/
Step 2: Organize Files in LLM Directory
After downloading, organize the files in ComfyUI/models/LLM/ as follows:
ComfyUI/models/LLM/
├── workflow-generator-q8_0.gguf # Main model (required)
├── workflow-generator/ # Main tokenizer (required)
│ ├── tokenizer.json
│ ├── tokenizer_config.json
│ ├── vocab.json
│ ├── merges.txt
│ ├── special_tokens_map.json
│ ├── added_tokens.json
│ ├── config.json
│ ├── generation_config.json
│ └── model.safetensors.index.json
├── paraphrase-multilingual-MiniLM-L12-v2/ # Embedding model (required)
│ ├── config.json
│ ├── model.safetensors
│ ├── modules.json
│ ├── sentence_bert_config.json
│ ├── config_sentence_transformers.json
│ ├── tokenizer.json
│ ├── tokenizer_config.json
│ ├── special_tokens_map.json
│ ├── sentencepiece.bpe.model
│ ├── unigram.json
│ └── 1_Pooling/
│ └── config.json
├── Qwen2.5-7B-Instruct-q8_0.gguf # NodeValidator model (optional)
└── Qwen2.5-7B-Instruct/ # NodeValidator tokenizer (optional)
├── tokenizer.json
├── tokenizer_config.json
├── vocab.json
├── merges.txt
├── config.json
└── generation_config.json
Important : The tokenizer directory name must match the model name (without .gguf extension and quantization suffix). The auto-detection code looks for:
workflow-generator-q8_0.gguf → workflow-generator/ tokenizer
Qwen2.5-7B-Instruct-q8_0.gguf → Qwen2.5-7B-Instruct/ tokenizer
Usage
Required Models
workflow-generator-q8_0.gguf + workflow-generator/ tokenizer - Always needed
paraphrase-multilingual-MiniLM-L12-v2/ - Always needed for semantic search
Optional Models
Qwen2.5-7B-Instruct-q8_0.gguf + Qwen2.5-7B-Instruct/ tokenizer - Only needed if using LLM refinement (use_llm_refinement=True)
Model Usage in ComfyUI-WorkflowGenerator
WorkflowGenerator Node : Uses workflow-generator-q8_0.gguf to generate workflow diagrams from natural language
NodeValidator Node :
Uses paraphrase-multilingual-MiniLM-L12-v2 for semantic search (always)
Uses Qwen2.5-7B-Instruct-q8_0.gguf for LLM refinement (optional, when use_llm_refinement=True)
WorkflowBuilder Node : No models needed (deterministic code)
Model Specifications
Workflow Generator Model
Format : GGUF (q8_0 quantization)
Base : Qwen2.5-14B
Size : ~8-9 GB (quantized)
Context Window : 131,072 tokens (128K) - Model architecture supports up to 131K tokens, though training used 16,384 token cutoff
Quantization : q8_0 (8-bit, good balance of quality and size)
Embedding Model
Format : SentenceTransformer (HuggingFace format)
Base : sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
Size : ~420 MB
Dimensions : 384 (embedding vector size)
Node Validator Model
Format : GGUF (q8_0 quantization)
Base : Qwen2.5-7B-Instruct
Size : ~4-5 GB (quantized)
Context Window : 32,768 tokens
Quantization : q8_0 (8-bit, good balance of quality and size)
System Requirements
VRAM :
Minimum: 8 GB (for workflow-generator with CPU offloading)
Recommended: 16+ GB (for both models on GPU)
RAM : 16+ GB recommended
Storage : ~15-16 GB for all models, tokenizers, and embedding model
Performance Tips
Use GGUF models : Smaller size and better VRAM efficiency than HuggingFace models
GPU Layers : Use "auto" setting for optimal GPU layer allocation
LLM Refinement : Only enable if you need higher accuracy (slower but more accurate)
Semantic Search Only : Faster execution, deterministic results (recommended for most use cases)
Troubleshooting
Model Not Found
Verify models are in ComfyUI/models/LLM/ directory
Check tokenizer directory name matches model name (without .gguf and quantization suffix)
Restart ComfyUI after moving files
Tokenizer Not Found
Ensure tokenizer directory exists with the correct name
Verify tokenizer files (tokenizer.json, tokenizer_config.json, vocab.json) are present
Check directory structure matches the expected format
Out of Memory
Reduce n_gpu_layers (try "auto" or lower number)
Use smaller quantization (q4_0 instead of q8_0) - note: you'll need to re-quantize
Set device_preference to "cpu" for some operations
Related Resources
ComfyUI-WorkflowGenerator : GitHub Repository
Original ComfyGPT Research : GitHub Repository
Research Paper : arXiv:2503.17671
Project Website : https://comfygpt.github.io/
Citation
If you use these models in your research, please cite the original ComfyGPT paper:
1 @article{huang2025comfygpt,
2 title={ComfyGPT: A Self-Optimizing Multi-Agent System for Comprehensive ComfyUI Workflow Generation},
3 author={Huang, Oucheng and Ma, Yuhang and Zhao, Zeng and Wu, Mingrui and Ji, Jiayi and Zhang, Rongsheng and Hu, Zhipeng and Sun, Xiaoshuai and Ji, Rongrong},
4 journal={arXiv preprint arXiv:2503.17671},
5 year={2025}
6 }
License
These models are provided for use with ComfyUI-WorkflowGenerator. Please refer to:
Original ComfyGPT repository for model training details and licensing
Qwen2.5 model licenses from HuggingFace
ComfyUI-WorkflowGenerator repository for usage terms
Support
For issues, questions, or contributions: