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Wednesday, July 17, 2024

Introducing Gemma Models in Keras

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Google has recently introduced a new family of artificial intelligence models known as Gemma. These state-of-the-art open models are built from the same research and technology used to create the Gemini models, marking a significant step forward in AI development.

We’re excited to announce that the Keras team has made these innovative Gemma models available in the KerasNLP collection. This integration will undoubtedly catalyze advancements in machine learning and AI applications.

What is Gemma?

Gemma is a set of lightweight, open AI models introduced by Google. The models are based on the infrastructure and technology components from the well-known Gemini models. Google is releasing model weights in two sizes: Gemma 2B and Gemma 7B. Each size is released with pre-trained and instruction-tuned variants.

Advantages of Gemma Models

The introduction of Gemma models offers several benefits for developers and researchers. Notably, these models come with a permissive commercial license and outperform other open models like Llama 2 and Mistral.

These smaller, open models can help developers and researchers build responsible AI applications. They also provide an opportunity for further exploration of sequence salience, an interpretability technique, to analyze different prompt engineering approaches.

Gemma Models in KerasNLP Collection

The inclusion of Gemma models in the KerasNLP collection is a significant event for the AI community. Keras, a popular open-source software library for neural networks, is widely recognized for its user-friendly and modular nature. The addition of Gemma to this collection will provide developers with more opportunities to leverage state-of-the-art AI models in their projects.

The introduction of Gemma models represents a significant advancement in AI technology. Their lightweight nature, coupled with their superior performance, makes them an excellent resource for developers and researchers seeking to create responsible and efficient AI applications.

With Gemma models now available in the KerasNLP collection, the future of AI development looks promising. We look forward to seeing the innovative applications that will emerge from this integration

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