How to finetune Llama 2 LLM

Llama 2 is a family of large language models (LLMs) developed by Meta AI with varying parameters from 7B to 70B. It offers improvements over its predecessor, Llama 1, and has a massive context length of 4K tokens. This guide explains how to fine-tune the Llama 2 - 7B model using the CodeAlpaca-20k Dataset through Monster API's No-Code LLM-Finetuner. The process involves selecting a language model, uploading a dataset, specifying hyperparameters, and submitting the fine-tuning job. By finetuning Llama 2, developers can tailor the pre-trained models to specific tasks, improving their accuracy, context awareness, and alignment with target applications. Monster API simplifies this process by providing an intuitive interface, optimizing memory usage, offering low-cost GPU access, and standardizing workflows. The outcome of fine-tuning Llama 2 using the CodeAlpaca-20k Dataset resulted in a coding chatbot with enhanced performance compared to the base model.