Fine vs. Refact.ai vs. StarCoder vs. python-sql Comparison Chart

Fine is an AI-powered development platform designed to assist startups by automating tasks throughout the software development lifecycle. It offers a range of AI agent workflows for coding, debugging, testing, and code review, allowing teams to ship daily improvements and resolve pull requests faster. Fine can autonomously create and implement code, conduct pull request reviews, generate tests, and handle common issues without constant human input. The platform integrates seamlessly with GitHub and supports asynchronous work, making it particularly suitable for fast-paced startups. With real-time feedback and live previews, Fine improves productivity and streamlines the development process.

StarCoder and StarCoderBase are Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks. Similar to LLaMA, we trained a ~15B parameter model for 1 trillion tokens. We fine-tuned StarCoderBase model for 35B Python tokens, resulting in a new model that we call StarCoder. We found that StarCoderBase outperforms existing open Code LLMs on popular programming benchmarks and matches or surpasses closed models such as code-cushman-001 from OpenAI (the original Codex model that powered early versions of GitHub Copilot). With a context length of over 8,000 tokens, the StarCoder models can process more input than any other open LLM, enabling a wide range of interesting applications. For example, by prompting the StarCoder models with a series of dialogues, we enabled them to act as a technical assistant.