LLM Finetuning UI Tool
2.1k 2026-04-30
lxe/simple-llm-finetuner
A beginner-friendly UI for fine-tuning large language models (LLMs) using the LoRA method on commodity NVIDIA GPUs.
Core Features
Beginner-friendly UI with explanations for each parameter.
Facilitates LoRA method via the PEFT library for efficient finetuning.
Simple dataset input by pasting into the UI, separated by double blank lines.
Adjustable parameters for both fine-tuning and inference processes.
Allows evaluation of the model's inference capabilities post-training.
Quick Start
git clone https://github.com/lxe/simple-llm-finetuner.git && cd simple-llm-finetuner && pip install -r requirements.txt && python app.pyDetailed Introduction
Simple LLM Finetuner offers a user-friendly graphical interface designed to democratize the fine-tuning of large language models. It utilizes the efficient LoRA method through the PEFT library, making it possible to train models on consumer-grade NVIDIA GPUs, even with modest VRAM. The tool simplifies dataset input, parameter configuration, and model evaluation, providing an accessible pathway for beginners to customize LLMs. Its intuitive design aims to lower the technical barrier for personalized AI model development and experimentation, enabling broader participation in the LLM ecosystem.