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 keisuke-miyako/bge-m3-doc-r2.2-gguf:Q8_0
# Run inference directly in the terminal:
llama cli -hf keisuke-miyako/bge-m3-doc-r2.2-gguf:Q8_0
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf keisuke-miyako/bge-m3-doc-r2.2-gguf:Q8_0
# Run inference directly in the terminal:
llama cli -hf keisuke-miyako/bge-m3-doc-r2.2-gguf:Q8_0
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 keisuke-miyako/bge-m3-doc-r2.2-gguf:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf keisuke-miyako/bge-m3-doc-r2.2-gguf:Q8_0
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 keisuke-miyako/bge-m3-doc-r2.2-gguf:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf keisuke-miyako/bge-m3-doc-r2.2-gguf:Q8_0
Use Docker
docker model run hf.co/keisuke-miyako/bge-m3-doc-r2.2-gguf:Q8_0
Quick Links

bge-m3-doc-r3 (GGUF q8_0)

Fine-tuned on 4D doc document embeddings. Dataset: keisuke-miyako/doc-2026-0610

Usage (llama.cpp)

./llama-embedding -m bge-m3-doc-r3-q8_0.gguf --prompt "your query"
Downloads last month
36
GGUF
Model size
0.6B params
Architecture
bert
Hardware compatibility
Log In to add your hardware

8-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support

Model tree for keisuke-miyako/bge-m3-doc-r2.2-gguf

Base model

BAAI/bge-m3
Quantized
(276)
this model