From Text to Code - Empowering Developers with Code Assistance Using StarCoder and GPT-4

Watch a 22-minute technical video comparing the capabilities of different Large Language Models (LLMs) for code generation, specifically focusing on the open-source 16B model StarCoder versus GPT-4. Dive into a detailed analysis of StarCoder, StarCoderBase, and StarChat's performance in generating Python code, with practical demonstrations including calculating sphere surface areas. Learn about StarCoder's architecture featuring 40 hidden layers, its training on 80+ programming languages and 35 billion Python tokens, and its sophisticated data cleaning process involving visual inspection and filtering of XML, HTML, JSON, and Jupyter Notebooks. Understand the model's infilling capabilities, byte pair encoding tokenization, and performance on code completion benchmarks, particularly in Python data science applications. Gain insights into the collaborative development efforts behind StarCoder and explore the potential of open-source alternatives to larger, closed-source language models for code generation.