This project showcases parameter-efficient fine-tuning of the LLaMA 3.2 (3B) language model using PEFT (Parameter-Efficient Fine-Tuning) and LoRA (Low-Rank Adaptation). It is optimized for minimal resource usage and trained on a domain-specific dataset to enhance performance in specialized tasks.
☆18Jun 1, 2025Updated 10 months ago
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