4AI/LS-LLaMA

A Simple but Powerful SOTA NER Model | Official Code For Label Supervised LLaMA Finetuning

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This project helps machine learning engineers and researchers fine-tune large language models (LLMs) for specific text classification and named entity recognition tasks. You provide text data with corresponding labels, and it outputs a specialized LLM capable of accurately classifying text or identifying entities within new text. It is designed for those who need to adapt powerful LLMs to their unique domain-specific datasets.

153 stars. No commits in the last 6 months.

Use this if you are a machine learning engineer or researcher looking to fine-tune LLaMA models for sequence classification (like sentiment analysis) or token classification (like named entity recognition) using your own labeled datasets.

Not ideal if you are an end-user without machine learning experience or if you need a pre-built application rather than a tool for model development.

natural-language-processing machine-learning-engineering text-classification named-entity-recognition large-language-models
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 18 / 25

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Stars

153

Forks

24

Language

Python

License

MIT

Last pushed

Mar 17, 2024

Commits (30d)

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