Abhi0323 / Fine-Tuning-LLaMA-2-with-QLORA-and-PEFTView external linksLinks
This project enhances the LLaMA-2 model using Quantized Low-Rank Adaptation (QLoRA) and other parameter-efficient fine-tuning techniques to optimize its performance for specific NLP tasks. The improved model is demonstrated through a Streamlit application, showcasing its capabilities in real-time interactive settings.
☆13Apr 18, 2024Updated last year
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