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  • JULY 16, 2025 / Cloud

    Stanford’s Marin foundation model: The first fully open model developed using JAX

    The Marin project aims to expand the definition of 'open' in AI to include the entire scientific process, not just the model itself, by making the complete development journey accessible and reproducible. This effort, powered by the JAX framework and its Levanter tool, allows for deep scrutiny, trust in, and building upon foundation models, fostering a more transparent future for AI research.

    Stanford Marin project in JAX
  • JULY 9, 2025 / Gemma

    T5Gemma: A new collection of encoder-decoder Gemma models

    T5Gemma is a new family of encoder-decoder LLMs developed by converting and adapting pretrained decoder-only models based on the Gemma 2 framework, offering superior performance and efficiency compared to its decoder-only counterparts, particularly for tasks requiring deep input understanding, like summarization and translation.

    T5Gemma: A New Collection of Encoder-Decoder Gemma Models
  • JUNE 24, 2025 / Kaggle

    Using KerasHub for easy end-to-end machine learning workflows with Hugging Face

    KerasHub enables users to mix and match model architectures and weights across different machine learning frameworks, allowing checkpoints from sources like Hugging Face Hub (including those created with PyTorch) to be loaded into Keras models for use with JAX, PyTorch, or TensorFlow. This flexibility means you can leverage a vast array of community fine-tuned models while maintaining full control over your chosen backend framework.

    How to load model weights from SafeTensors into KerasHub for multi-framework machine learning
  • FEB. 19, 2025 / Gemma

    Introducing PaliGemma 2 mix: A vision-language model for multiple tasks

    PaliGemma 2 mix, an upgraded vision-language model, is now available, offering capabilities like image captioning, OCR, and object detection in various sizes.

    Paligemma 2 Mix