#1818th of 19 in Training and fine-tuning
easy-dataset
Turns documents into LLM fine-tuning and evaluation datasets
- Stars
- 15k
- License
- custom license
- Last commit
- May 2026
- Last release
- Apr 2026
- Language
- JavaScript
Missed the latest GitHub check; these facts may be older.
Overview
Easy Dataset parses PDF, Markdown, DOCX, TXT and EPUB files, splits them into chunks, and uses an LLM to generate questions, answers and chain-of-thought for single-turn, multi-turn or image QA datasets. It also builds evaluation sets with a judge model and a double-blind arena, and exports to Alpaca or ShareGPT, LLaMA Factory configs, or Hugging Face. It runs as a web app on port 1717 or as a desktop client.
Who it is for: Engineers building fine-tuning or evaluation datasets from domain documents
Strengths
- Covers raw documents to Alpaca/ShareGPT export in JSON or JSONL
- Generates evaluation sets with judge-model scoring and a human blind test arena
- Works with any OpenAI-format API, plus Ollama for local models
- Generates LLaMA Factory configs and uploads to Hugging Face Hub
Weaknesses
- AGPL-3.0 license restricts closed-source network deployment
- Output quality depends on an external LLM API or separate local model server
- Many tutorials and community guides are Chinese-language video or wiki links
- Local database file storage; no multi-user setup described
What it needs
- no GPU
- Docker + Compose
- Needs OpenAI-compatible LLM API or Ollama
- Models: OpenAI-compatible APIs, Ollama, OpenRouter, Zhipu AI, Alibaba Bailian
- port 1717
Also in Training and fine-tuning
See all 19| Rank | Project | Score |
|---|---|---|
| 1 | unslothDesktop and web app to run, fine-tune and export open models | 88 out of 100 |
| 2 | deepspeedPyTorch library for distributed training of large models with ZeRO | 82 out of 100 |
| 3 | verlReinforcement learning training library for LLM post-training with PPO and GRPO | 77 out of 100 |
| #4 | llamafactoryFine-tuning toolkit for 100+ LLMs with a CLI and Gradio web UI | 75 out of 100 |
| #5 | peftPython library for LoRA and other parameter-efficient fine-tuning of Transformers models | 74 out of 100 |