lxe/simple-llm-finetuner
Simple UI for LLM Model Finetuning observed · 2026-08-28
Health v2 · maintenance only
30/100
- Activity 0
- Release rhythm 35
- Longevity 90
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1260
- days_rel: n/a
- days_push: 986
- n_releases_24m: 0
Adoption not part of the score
2054 stars · 131 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A beginner-friendly Gradio web UI for fine-tuning LLMs (LLaMA, GPT-2) using LoRA via the Hugging Face PEFT library on consumer NVIDIA GPUs. It lets users paste datasets, adjust training parameters, and run inference from the browser.
Use cases
- fine-tune llama on my own dataset with a simple ui
- train a language model with lora on a single gpu
- beginner-friendly llm finetuning tool
- run peft finetuning in google colab
- customize an llm with a small training dataset
When to choose
- you want a minimal, no-code UI to experiment with LoRA fine-tuning on a 16GB GPU or Colab T4
When to avoid
- the project is explicitly dead and unmaintained - use LLaMA-Factory, unsloth, or text-generation-webui instead
- you need production-grade or actively supported fine-tuning workflows
- you lack an NVIDIA GPU or WSL/Linux environment
Facets
application · maturity abandoned
llm-training machine-learning gui large-language-models machine-learning artificial-intelligence python llm-finetuning lora peft gradio huggingface colab beginner-friendly linux gpu web-server
1 source
- readme: https://github.com/lxe/simple-llm-finetuner · fetched 2026-08-28 · 28bb797edc00
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| lxe/simple-llm-finetuner | main | 30 |
For agents
markdown · JSON · MCP: product_card(name="lxe/simple-llm-finetuner")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem