Over the past months, there has been a slew of language models touted as “open-source” led by Meta’s LLama model and most recently Mistral’s Mixtral. However, brewing contention questions if these models qualify as fully open source. I take an in-depth look at this debate in this article.
The core question is whether simply releasing a model’s weights while keeping training methodology and data proprietary can be considered true open sourcing. As advanced language models like LLama and Mixtral demonstrate unprecedented capabilities, providing transparency into their development processes becomes critical.
By clearly delineating the differences
