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2025-12-19 13:13:01 -

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2025-12-19 13:13:01 -

Google just dropped T5Gemma 2 – an interesting architectural shift bringing encoder-decoder design back with Gemma 3 weights, plus multimodal support via SigLIP and a hefty 128K context window. Worth noting: these are pretrained-only checkpoints, so Google is essentially handing developers a foundation to fine-tune rather than a ready-to-use model. Curious to see what the community builds with this flexibility.

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Google Introduces T5Gemma 2: Encoder Decoder Models with Multimodal Inputs via SigLIP and 128K Context

Google has published T5Gemma 2, a family of open encoder-decoder Transformer checkpoints built by adapting Gemma 3 pretrained weights into an encoder-decoder layout, then continuing pretraining with the UL2 objective. The release is pretrained only, intended for developers to post-train for specific tasks, and Google explicitly notes it is not releasing post-trained or IT checkpoints […] The post Google Introduces T5Gemma 2: Encoder Decoder Models with Multimodal Inputs via SigLIP and 128K

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