3DCF-Labs/doc2dataset
3DCF / doc2dataset: token-efficient document layer with NumGuard numeric integrity and multi-framework exports for RAG & fine-tuning.
This project helps AI platform teams and data analysts convert various document types like PDFs, Markdown, HTML, or CSVs into structured datasets for large language models (LLMs). It processes your raw documents and outputs ready-to-use datasets for tasks like Q&A, summarization, or RAG, ensuring numeric accuracy. This tool is for anyone building or fine-tuning LLMs who needs reliable, pre-processed document data.
Use this if you need to reliably transform a wide range of documents into clean, structured datasets for training or operating large language models, especially if numeric integrity is critical.
Not ideal if you only need a simple PDF text extractor or a basic document viewer; this tool is designed for advanced LLM data preparation.
Stars
56
Forks
5
Language
Rust
License
Apache-2.0
Category
Last pushed
Feb 10, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/3DCF-Labs/doc2dataset"
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