This is a community-quantized version of the Gemma 4 model using E4B (4-bit embedding) weights and 16-bit activations. It is instruction-tuned and includes a specialized chat template. The model is hosted on Hugging Face and intended for efficient inference in text generation applications.
In the Foundation models & chat space, Gemma 4 E4B It W4A16 takes a focused approach. It focuses on running large Gemma models with reduced memory footprint through 4-bit quantization. Gemma 4 E4B It W4A16 is an open-source project aimed at machine learning developers. The project is open source (Open Source). It ships for the web, the command line, and API.
ciocan builds and maintains Gemma 4 E4B It W4A16. The category is crowded — PulseGate's index counts 25 comparable projects. Key capabilities include Quantized Weights, Instruction Tuning, and Chat Template.
Summary written by a language model from the project’s public pages.
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