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metricspace
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embeddinggemma-300m-q4k

GGUF
embeddings
code-search
retrieval
greppy
Model card Files
xet
 Community
How to use from
llama.cpp
Install (macOS, Linux) 
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf metricspace/embeddinggemma-300m-q4k
# Run inference directly in the terminal:
llama cli -hf metricspace/embeddinggemma-300m-q4k
Install from WinGet (Windows) 
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf metricspace/embeddinggemma-300m-q4k
# Run inference directly in the terminal:
llama cli -hf metricspace/embeddinggemma-300m-q4k
Use pre-built binary 
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf metricspace/embeddinggemma-300m-q4k
# Run inference directly in the terminal:
./llama-cli -hf metricspace/embeddinggemma-300m-q4k
Build from source code 
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf metricspace/embeddinggemma-300m-q4k
# Run inference directly in the terminal:
./build/bin/llama-cli -hf metricspace/embeddinggemma-300m-q4k
Use Docker 
docker model run hf.co/metricspace/embeddinggemma-300m-q4k
Quick Links

EmbeddingGemma-300M — Q4_K GGUF (greppy runtime asset)

A Q4_K GGUF quantization of Google's EmbeddingGemma-300M, distributed as the embedded semantic-search backend of greppy, a local code-navigation tool for coding agents. greppy embeds this file directly in its binary and runs it on device (native Rust + vendored Metal/CUDA kernels — no llama.cpp runtime, Python, or model server) to power greppy semantic-search: finding code by meaning when the symbol name is unknown.

  • Base model: google/embeddinggemma-300m (includes the dense post-processing modules for sentence-transformers-compatible embeddings).
  • Quantization: Q4_K, from a pinned, byte-identical snapshot of cduk/embeddinggemma-300m-GGUF-with-dense-modules.
  • Use in greppy: query- and source-span embeddings for on-device retrieval.

License — Gemma Terms of Use (NOT Apache)

This model is a Model Derivative of Gemma and is provided under and subject to the Gemma Terms of Use, not an open-source license. By using or redistributing these files you agree, as an enforceable condition, that you will not use them for any purpose prohibited by the Gemma Prohibited Use Policy, and that any onward distribution carries these same restrictions, a copy of the Gemma Terms, and the notice below.

The binding terms, the Google notice, and the record of modifications are included in this repository:

  • GEMMA-TERMS.html
  • GEMMA-PROHIBITED-USE-POLICY.html
  • EMBEDDINGGEMMA-NOTICE.txt
  • EMBEDDINGGEMMA-MODIFICATIONS.txt
  • EMBEDDINGGEMMA-PROVENANCE.json

"Gemma" is a trademark of Google LLC. This is a community quantization for greppy and is not endorsed by or affiliated with Google.

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