Our first paper: “Deriving Coding-Specific Sub-Models from LLMs using Resource-Efficient Pruning”
We are happy to announce that our first paper will appear in the Proceedings of the Second International Workshop on Large Language Models for Code (LLM4Code). The paper title is “Deriving Coding-Specific Sub-Models from LLMs using Resource-Efficient Pruning“, and this is joint work with Laura Puccioni (now at Spotify), Alireza Farshin (now at NVIDIA), Mariano … Continue reading “Our first paper: “Deriving Coding-Specific Sub-Models from LLMs using Resource-Efficient Pruning””