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Fine-Tuning-LLaMA-2-with-QLORA-and-PEFT

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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.

Creat2024-03-26T11:59:14
Update2025-02-11T11:43:31
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