EmbeddingGemma 300M Sentence Transformers
Collection
3 items • Updated
How to use sabafallah/embeddinggemma-300m-sentence-transformers-gguf with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("sabafallah/embeddinggemma-300m-sentence-transformers-gguf")
sentences = [
"The weather is lovely today.",
"It's so sunny outside!",
"He drove to the stadium."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]How to use sabafallah/embeddinggemma-300m-sentence-transformers-gguf with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0 # Run inference directly in the terminal: llama cli -hf sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0 # Run inference directly in the terminal: llama cli -hf sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0
# 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 sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0
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 sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0
docker model run hf.co/sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0
How to use sabafallah/embeddinggemma-300m-sentence-transformers-gguf with Ollama:
ollama run hf.co/sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0
How to use sabafallah/embeddinggemma-300m-sentence-transformers-gguf with Docker Model Runner:
docker model run hf.co/sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0
How to use sabafallah/embeddinggemma-300m-sentence-transformers-gguf with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull sabafallah/embeddinggemma-300m-sentence-transformers-gguf:Q8_0
lemonade run user.embeddinggemma-300m-sentence-transformers-gguf-Q8_0
lemonade list
This GGUF Model includes all sentence-transformers (dense) modules.
Recommended way to run this model:
llama-server -hf sabafallah/embeddinggemma-300m-sentence-transformers-gguf --embeddings
Then the endpoint can be accessed at http://localhost:8080/embedding, for
example using curl:
curl --request POST \
--url http://localhost:8080/embedding \
--header "Content-Type: application/json" \
--data '{"input": "task: sentence similarity | query: Hello embeddings"}' \
--silent
Alternatively, the llama-embedding command line tool can be used:
llama-embedding -hf sabafallah/embeddinggemma-300m-sentence-transformers-gguf --verbose-prompt -p "task: sentence similarity | query: Hello embeddings"
8-bit
Base model
google/embeddinggemma-300m