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Gemma 4 31B It Assistant

Hugging Face | GitHub | MTP Documentation

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Text model
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896 MB
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vmodel
Updated
Sep 15, 2026
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10
Source
Hugging Face

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Hugging Face | GitHub | MTP Documentation

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1 source
Hugging FacePrimaryVersion ce6e06afd000a22bbad38f2ce095804297944575
huggingface.co/jsm40/gemma-4-31B-it-assistant/tree/ce6e06afd000a22bbad38f2ce095804297944575

Verified Sep 15

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model.safetensors

safetensors · 896 MB · SHA-256 9f80df6099fa…a1da · Hugging Face

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--- library_name: transformers license: apache-2.0 license_link: https://ai.google.dev/gemma/docs/gemma_4_license pipeline_tag: any-to-any --- <div align="center"> <img src=https://ai.google.dev/gemma/images/gemma4_banner.png> </div> <p align="center"> <a href="https://huggingface.co/collections/google/gemma-4" target="_blank">Hugging Face</a> | <a href="https://github.com/google-gemma" target="_blank">GitHub</a> | <a href="https://ai.google.dev/gemma/docs/mtp/mtp" target="_blank">MTP Documentation</a> <br> <b>License</b>: <a href="https://ai.google.dev/gemma/docs/gemma_4_license" target="_blank">Apache 2.0</a> | <b>Authors</b>: <a href="https://deepmind.google/models/gemma/" target="_blank">Google DeepMind</a> </p> > [!Note] > This model card is for the Multi-Token Prediction (MTP) drafters for the Gemma 4 models. MTP is implemented by extending the base model with a smaller, faster draft model. When used in a Speculative Decoding pipeline, the draft model predicts several tokens ahead, which the target model then verifies in parallel. This results in significant decoding speedups (up to 3x) while guaranteeing the exact same quality as standard generation, making these checkpoints perfect for low-latency and on-device applications. Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on small models) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages. Featuring both Dense and Mixture-of-Experts (MoE) architectures, Gemma 4 is well-suited for tasks like text generation, coding, and reasoning. The models are available in four distinct sizes: **E2B**, **E4B**, **26B A4B**, and **31B**. Their diverse sizes make them deployable in environments ranging from high-end phones to laptops and servers, democratizing access to state-of-the-art AI. Gemma 4 introduces key **capability and architectural advancements**: * **Reasoning** – All models in the family are designed as highly capable reasoners, with configurable thinking modes. * **Extended Multimodalities** – Processes Text, Image with variable aspect ratio and resolution support (all models), Video, and Audio (featured natively o...

Source context: 10 downloads · 0 likes · Pipeline any-to-any · Library transformers · Repo jsm40/gemma-4-31B-it-assistant