This Hugging Face repository provides GGUF-format, instruction-tuned Gemma 4 E2B model weights for local inference. Developers can download and run the quantized model with compatible runtimes such as llama.cpp.
In the Quantised & converted weights space, Gemma 4 E2B It takes a focused approach. It focuses on running an instruction-tuned Gemma language model locally in a quantized format. It is built as an open-source project for developers and machine learning practitioners. Gemma 4 E2B It is open source under the Open Source license. Gemma 4 E2B It is available on the command line, and it can be self-hosted.
ggml-org builds and maintains Gemma 4 E2B It, and it first shipped in 2026. Development happens publicly on GitHub with 30 stars and 136 commits in the last 90 days. It competes in a saturated segment with 25 similar projects in PulseGate's index. Among its 5 catalogued features are quantized weights, GGUF format, and instruction tuning.
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