How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf rizkysulaeman/Embedding-Gemma-300m:
# Run inference directly in the terminal:
llama-cli -hf rizkysulaeman/Embedding-Gemma-300m:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf rizkysulaeman/Embedding-Gemma-300m:
# Run inference directly in the terminal:
llama-cli -hf rizkysulaeman/Embedding-Gemma-300m:
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 rizkysulaeman/Embedding-Gemma-300m:
# Run inference directly in the terminal:
./llama-cli -hf rizkysulaeman/Embedding-Gemma-300m:
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 rizkysulaeman/Embedding-Gemma-300m:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf rizkysulaeman/Embedding-Gemma-300m:
Use Docker
docker model run hf.co/rizkysulaeman/Embedding-Gemma-300m:
Quick Links

Embedding-Gemma-300m - GGUF

This sentence-transformers model was finetuned and converted to GGUF format using Unsloth.

Available Model files:

  • embeddinggemma-300m.Q5_K_M.gguf
  • embeddinggemma-300m.Q8_0.gguf
  • embeddinggemma-300m.Q4_K_M.gguf

This was trained 2x faster with Unsloth

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