Gemma 4 E2B It GGUF

--- base_model: - google/gemma-4-E2B-it datasets: - eaddario/imatrix-calibration language: - en license: - apache-2.0 pipeline_tag: any-to-any tags: - gguf - quant - experimental - target_bpw --- # Experimental global target bits‑per‑weight quantization of [google/gemma-4-E2B-it][base] Using **non-standard** (forked) [LLaMA C++][llm] release [b8838][llm-rel] for quantization. Original model: [google/gemma-4-E2B-it][mdl] From the original model creators: > <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://blog.google/innovation-and-ai/technology/developers-tools/gemma-4/" target="_blank">Launch Blog</a> | > <a href="https://ai.google.dev/gemma/docs/core" target="_blank">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> > > 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 on the E2B and E4B models). > > * **Diverse & Efficient Architectur...