Code Llama is a collection of base and instruct fine-tuned models with 7B, 13B, 34B and 70B parameters. Code Llama reaches state-of-the-art performance among open models on several code benchmarks, with scores of up to 67% and 65% on HumanEval and MBPP, respectively. Notably, Code Llama - Python 7B outperforms Llama 2 70B on HumanEval and MBPP, and all our models outperform every other publicly available model on MultiPL-E. We release Code Llama under a permissive license that allows for both research and commercial use. This talk will present the different types of Code Llama models, and show how they can be used in practice for research and applications.

Baptiste is a research scientist at Meta AI in Paris working in the code generation team. He works on large language models, with a special interest in applications to code. Baptiste contributed to Llama and started Code Llama. Before that, he worked on model pre-training and machine translation for programming languages.