Extensions/ComfyUI_LFM2-350M
ComfyUI Extension

ComfyUI_LFM2-350M

A custom node for ComfyUI to load and use the LFM2-350M model trained to work as a prompt enhancer for z-image turbo or any other long token model.

By marduk191·Created 7 months ago·Updated 7 months ago· 2
marduk191/ComfyUI_LFM2-350M
Nodes2
On cloudLocal install
CategoryLiquidAI/LFM2
Stars2
Updated7 months ago

Nodes (2)

LiquidAI LFM-2-350M Generator
LiquidAI/LFM2
LiquidAI LFM-2-350M Loader
LiquidAI/LFM2
Readme

ComfyUI LFM2-350M Node

A custom node for ComfyUI to load and use my custom tuned LFM2-350M model trained on 60k base pairs to work as a prompt enhancer for z-image turbo or any other long token model.

Features

  • Load from HuggingFace or a local path
  • Supports fine-tuned models saved with torch.compile() (automatically fixes _orig_mod. weight prefix)
  • Configurable generation parameters (temperature, top_p, top_k, min_p, repetition_penalty)
  • System prompt and user prompt inputs

Installation

  1. Clone this repository into your ComfyUI custom_nodes folder:

    cd ComfyUI/custom_nodes
git clone https://github.com/marduk191/ComfyUI_LFM2-350M.git

  2. Install dependencies:

    cd ComfyUI_LFM2-350M
pip install -r requirements.txt

  3. Restart ComfyUI.

Nodes

LiquidAI LFM-2-350M Loader

Loads the model and tokenizer.

| Input | Description | |-------|-------------| | repo_id | HuggingFace repository ID (default: marduk191/lfm2-350m-dp-marduk191) | | local_path | Optional local path to a pre-downloaded/fine-tuned model | | precision | Model precision: bf16, fp16, fp32, or auto | | device | cuda or cpu |

LiquidAI LFM-2-350M Generator

Generates text based on prompts.

| Input | Description | |-------|-------------| | model_context | Connect to Loader's model output | | tokenizer | Connect to Loader's tokenizer output | | system_prompt | System instructions for the model | | prompt | User input text | | max_new_tokens | Maximum tokens to generate (1-4096) | | temperature | Randomness control (default: 0.3) | | top_p | Nucleus sampling parameter | | top_k | K sampling parameter | | min_p | Minimum probability (default: 0.15) | | repetition_penalty | Penalty for repeating tokens (default: 1.05) |

Recommended Parameters

For best results with LFM2-350M:

  • temperature: 0.3
  • min_p: 0.15
  • repetition_penalty: 1.05

Requirements

  • Python 3.10+
  • PyTorch 2.0+
  • Transformers 4.55+
  • CUDA GPU recommended

Credits

License

MIT License