Gemma 4 E2B It BF16

--- library_name: transformers license: apache-2.0 license_link: https://ai.google.dev/gemma/docs/gemma_4_license pipeline_tag: any-to-any --- > **Note:** This repository is an **archived mirror** and is **not** the original upstream source. > The original model, weights, and documentation are developed and maintained by **Google DeepMind**. > > All hosted model weights are **unmodified**. > > The model is released under the **Apache License, Version 2.0**, which permits use, modification, and redistribution under its terms. > > *This repository is not affiliated with, endorsed by, or sponsored by Google DeepMind.* <p align="center"> <a href="https://huggingface.co/collections/google/gemma-4" target="_blank"> <img src="https://img.shields.io/badge/Models-Hugging%20Face-yellow?style=flat-square"> </a> <a href="https://github.com/google-gemma" target="_blank"> <img src="https://img.shields.io/badge/Source-GitHub-181717?style=flat-square"> </a> <a href="https://blog.google/innovation-and-ai/technology/developers-tools/gemma-4/" target="_blank"> <img src="https://img.shields.io/badge/Blog-Launch-lightgrey?style=flat-square"> </a> <a href="https://ai.google.dev/gemma/docs/core" target="_blank"> <img src="https://img.shields.io/badge/Docs-Official-0A66C2?style=flat-square"> </a> <a href="https://ai.google.dev/gemma/docs/gemma_4_license" target="_blank"> <img src="https://img.shields.io/badge/License-Apache%202.0-red?style=flat-square"> </a> <a href="https://deepmind.google/models/gemma/" target="_blank"> <img src="https://img.shields.io/badge/Author-Google%20DeepMind-blue?style=flat-square"> </a> </p> 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, democratizin...