StarCoder vs GPT-4

StarCoder is an innovative Large Language Model for Code (Code LLM) presented by Hugging Face, designed to revolutionize the way we work with programming languages. Trained on an extensive range of permissively licensed data gathered from GitHub, StarCoder understands and processes over 80 programming languages, Git commits, GitHub issues, and Jupyter notebooks. With its ~15B parameter model, StarsCoder is fine-tuned using 35B Python tokens, delivering unparalleled code completion, modification, and explanation capabilities. The model notably demonstrates superior performance in benchmarks against other open-source and proprietary Code LLMs like OpenAI's CodeX. StarCoder's advanced features include an extensive context length, the ability to function as a sophisticated technical assistant, and the promise of safe use through measures like PII redaction and novel attribution tracing. Additionally, StarCoder is being made accessible under the OpenRAIL license, encouraging widespread integration and adaptation to suit a variety of company products and community projects.

GPT-4 is the latest milestone in OpenAI’s effort in scaling up deep learning.

GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks. For example, it passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5’s score was around the bottom 10%. We’ve spent 6 months iteratively aligning GPT-4 using lessons from our adversarial testing program as well as ChatGPT, resulting in our best-ever results (though far from perfect) on factuality, steerability, and refusing to go outside of guardrails.

GPT-4 is more creative and collaborative than ever before. It can generate, edit, and iterate with users on creative and technical writing tasks, such as composing songs, writing screenplays, or learning a user’s writing style.