sh0416/llama-classification

Text classification with Foundation Language Model LLaMA

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This is a codebase for research scientists and machine learning engineers to conduct experiments on text classification using the LLaMA foundation model. It takes raw text data as input and outputs predicted categories or labels for each text, along with evaluation metrics like accuracy. The primary users are researchers focused on evaluating and comparing large language model performance on classification tasks.

113 stars. No commits in the last 6 months.

Use this if you are a researcher or ML engineer needing to implement and experiment with LLaMA for text classification, especially when exploring different probabilistic methods like 'Direct' or 'Channel' approaches.

Not ideal if you are looking for a plug-and-play solution for general text classification without deep dives into model architecture or experimental setups, or if you don't have access to substantial GPU resources.

natural-language-processing machine-learning-research text-categorization large-language-models model-evaluation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 11 / 25

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Stars

113

Forks

9

Language

Python

License

GPL-3.0

Last pushed

Mar 19, 2023

Commits (30d)

0

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