A quantized Gemma 3 27B instruction-tuned model checkpoint for local inference. It supports text and image inputs and is intended for developers running the model with compatible Transformers or AWQ tooling.
Gemma 3 27b It sits in PulseGate's Quantised & converted weights category. It focuses on running an instruction-tuned multimodal language model locally with reduced memory requirements. It is built as an open-source project for developers. The project is open source (Apache-2.0). It ships for the web and the command line, and it can be self-hosted.
It is developed by gaunernst, and it first shipped in 2018. The project is developed in the open on GitHub with 36.1k stars and 1.8k commits in the last 90 days. It operates in a well-populated space: PulseGate tracks 16 similar projects. Among its 6 catalogued features are text generation, image understanding, and instruction tuning.
Summary written by a language model from the project’s public pages.
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