IAAR-Shanghai/Grimoire

Grimoire is All You Need for Enhancing Large Language Models

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Emerging

This project helps improve how well smaller, less powerful language models can learn from examples. It takes examples from a strong language model and distills the key learning into a 'grimoire' which is then used by a weaker language model to perform tasks. This is for AI/ML researchers and engineers working with language models who need to get better performance out of smaller models on specific tasks.

117 stars. No commits in the last 6 months.

Use this if you need to boost the in-context learning capabilities of smaller language models to achieve performance levels similar to or even exceeding much larger models on specific tasks.

Not ideal if you are working exclusively with the largest, most powerful language models and don't need to transfer learning to smaller models.

AI-research natural-language-processing language-model-fine-tuning model-optimization in-context-learning
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

117

Forks

14

Language

Python

License

Apache-2.0

Last pushed

Feb 29, 2024

Commits (30d)

0

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