Google Launches Two New Open LLMs

Barely a week after launching the latest iteration of its Gemini models, Google today announced the launch of Gemma, a new family of lightweight open-weight models. From a report: Starting with Gemma 2B and Gemma 7B, these new models were "inspired by Gemini" and are available for commercial and research usage. Google did not provide us with a detailed paper on how these models perform against similar models from Meta and Mistral, for example, and only noted that they are "state-of-the-art." The company did note that these are dense decoder-only models, though, which is the same architecture it used for its Gemini models (and its earlier PaLM models) and that we will see the benchmarks later today on Hugging Face's leaderboard. To get started with Gemma, developers can get access to ready-to-use Colab and Kaggle notebooks, as well as integrations with Hugging Face, MaxText and Nvidia's NeMo. Once pre-trained and tuned, these models can then run everywhere. While Google highlights that these are open models, it's worth noting that they are not open-source. Indeed, in a press briefing ahead of today's announcement, Google's Janine Banks stressed the company's commitment to open source but also noted that Google is very intentional about how it refers to the Gemma models.

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