Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.
Open source
24 alternativesFastDatasets
FastDatasets helps create training datasets for large language models.
About FastDatasets
FastDatasets is an open-source Python tool for building training datasets for large language models from your own documents. It splits documents into chunks, generates questions from the content, and uses an LLM to produce answers, then exports the result as Alpaca or ShareGPT datasets ready for supervised fine-tuning. It also supports knowledge distillation from existing HuggingFace datasets and instruction augmentation, and can be run through a command line, a Python API, or a local web interface. The tool requires a Python 3.8+ environment and configuration of an external LLM API (API key, base URL and model name) via a .env file or environment variables, so processing depends on that provider. A hosted demo is offered for quick trials, while batch processing and full functionality are described as available in the local version. The project is licensed under Apache 2.0 and installed from PyPI as fastdatasets-llm.
Key features
- Generates question-answer training datasets from uploaded documents
- Supports PDF, Word, Markdown and plain-text document input
- Exports Alpaca and ShareGPT formats, with JSONL file output
- Knowledge distillation from HuggingFace datasets and instruction augmentation
- Usable via web interface, command line, or Python API
- Configurable chunk size, concurrency, chain-of-thought and questions per chunk
Best for: Developers and researchers who want to turn their own documents or existing datasets into fine-tuning data for large language models.
Good for
- Apache 2.0 licensed open-source package installable with pip
- Can process individual files, whole directories and multiple uploads in batch
- Offers both a zero-configuration hosted demo and an unrestricted local version
Watch out for
- Requires configuring an external LLM API key, base URL and model name before use
- The hosted Spaces version is described as for trial and demonstration only
- Troubleshooting notes that large documents or batches can run into memory or API timeout limits
FastDatasets at a glance
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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FastDatasets FAQ
What document formats can I feed into FastDatasets?
PDF, Word (.docx), Markdown and plain text, along with other common document formats.
What dataset formats does it output?
Alpaca and ShareGPT datasets, with JSONL file output available; intermediate chunk, question, answer and optimized files are also written to the output directory.
Do I need my own LLM API?
Yes. You configure LLM_API_KEY, LLM_API_BASE and a model name in a .env file or environment variables, or pass credentials directly in the Python call.
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