cross-posted from: https://lemmy.world/post/1305651
OpenLM-Research has Released OpenLLaMA: An Open-Source Reproduction of LLaMA
TL;DR: OpenLM-Research has released a public preview of OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA. We are releasing a series of 3B, 7B and 13B models trained on different data mixtures. Our model weights can serve as the drop in replacement of LLaMA in existing implementations.
In this repo, OpenLM-Research presents a permissively licensed open source reproduction of Meta AI's LLaMA large language model. We are releasing a series of 3B, 7B and 13B models trained on 1T tokens. We provide PyTorch and JAX weights of pre-trained OpenLLaMA models, as well as evaluation results and comparison against the original LLaMA models. The v2 model is better than the old v1 model trained on a different data mixture.
This is pretty incredible news for anyone working with LLaMA or other open-source LLMs. This allows you to utilize the vast ecosystem of developers, weights, and resources that have been created for the LLaMA models, which are very popular in many AI communities right now.
With this, anyone can now hop into LLaMA R&D knowing they have avenues to utilize it within their projects and businesses (commercially).
Big shoutout to the team who made this possible (OpenLM-Research). You should support them by visiting their GitHub and starring the repo.
A handful of varying parameter models have been released by this team, some of which are already circulating and being improved upon.
Yet another very exciting development for FOSS! If I recall correctly, Mark Zuckerberg mentioned in his recent podcast with Lex Fridman that the next official version of LLaMA from Meta will be open-source as well. I am very curious to see how this model develops this coming year.
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Hi there! Looks like you linked to a Lemmy community using an URL instead of its name, which doesn't work well for people on different instances. Try fixing it like this: !fosai@lemmy.world
Good bot, I will do that next time.