Metadata-Version: 2.1
Name: distilabel
Version: 0.1.0rc2
Summary: AI Feedback (AIF) framework
Project-URL: Documentation, https://github.com/argilla/distilabel#readme
Project-URL: Issues, https://github.com/argilla/distilabel/issues
Project-URL: Source, https://github.com/argilla/distilabel
Author-email: Argilla <admin@argilla.io>
License-Expression: MIT
License-File: LICENSE
Keywords: alignment,annotation,llm
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
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Requires-Dist: datasets>=2.14.0
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Provides-Extra: argilla
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Provides-Extra: hf-inference-endpoints
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Provides-Extra: hf-transformers
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Provides-Extra: llama-cpp
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Description-Content-Type: text/markdown

<div align="center">
 <h1>⚗️ distilabel</h1>
 <p><em>AI Feedback (AIF) framework in Python</em></p>
</div>

## What's `distilabel`?

`distilabel` is a Python framework for building datasets with AI for LLM fine-tuning, evaluation, and alignment. 

It gives an extensible and scalable framework for AI Feedback (AIF), Language Model (LM) alignment and model distillation, building on state of the art approaches such as UltraFeedback or JudgeLM.
