How to use Uncino/bge-m3-multivector-gguf with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Uncino/bge-m3-multivector-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 Uncino/bge-m3-multivector-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 Uncino/bge-m3-multivector-gguf:F16 # Run inference directly in the terminal: llama cli -hf Uncino/bge-m3-multivector-gguf:F16
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Uncino/bge-m3-multivector-gguf:F16 # Run inference directly in the terminal: llama cli -hf Uncino/bge-m3-multivector-gguf:F16
# 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 Uncino/bge-m3-multivector-gguf:F16 # Run inference directly in the terminal: ./llama-cli -hf Uncino/bge-m3-multivector-gguf:F16
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 Uncino/bge-m3-multivector-gguf:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Uncino/bge-m3-multivector-gguf:F16
docker model run hf.co/Uncino/bge-m3-multivector-gguf:F16
How to use Uncino/bge-m3-multivector-gguf with Ollama:
ollama run hf.co/Uncino/bge-m3-multivector-gguf:F16
How to use Uncino/bge-m3-multivector-gguf with Docker Model Runner:
How to use Uncino/bge-m3-multivector-gguf with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Uncino/bge-m3-multivector-gguf:F16
lemonade run user.bge-m3-multivector-gguf-F16
lemonade list
