Stable Code: An Optimized AI for Software Engineering
In comparison to Meta's Codelama, which has 7 billion parameters, our smaller but stable code model, at 3 billion parameters, is a powerhouse. It's 60% smaller in size which means it can run on less powerful hardware, and speedwise, it outperforms others. Not only that, but it also generates high-quality code in multiple languages more effectively.
The trick is that we used a trusted LLM 3 billion foundation model that has been trained on four trillion tokens and fine-tuned it using software engineering data, along with code, of course. Remarkably, the smaller size of this model allows it to operate privately on your everyday laptops, even those without specialized GPUs. On top of this, it's capable of handling 16,000 tokens; that's a lot. Here's where it gets even better: using Meta's tactic of rotary embeddings, you have the opportunity to expand the input context window to a massive 100,000 tokens.
Way more than you'd need for most coding projects. Lastly, our stable code got its smarts from training on data from the 18 most popular programming languages on Stack Overflow 2023.
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