crux82/CLiC-it_2023_tutorial
This repository hosts materials from the CLiC-IT 2023 tutorial
This project helps machine learning researchers and practitioners efficiently customize Large Language Models (LLMs) for specific natural language processing tasks. It takes raw text data from various tasks, processes it into special prompts, and then fine-tunes an LLM like LLaMA to produce tailored text outputs for those tasks. The end-user is anyone developing or applying LLMs who needs to adapt them without requiring supercomputing resources.
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Use this if you need to fine-tune a Large Language Model for multiple text-based tasks efficiently, especially if you have 'modest' hardware resources like a single 16GB GPU.
Not ideal if you are looking for a plug-and-play solution without any technical background in machine learning or model training.
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Jun 05, 2024
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