Embedding/Reranking Models
Collection
2 items • Updated
How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf LeadingPoint/R3-rerank-0.6b-GGUF:# Run inference directly in the terminal:
llama cli -hf LeadingPoint/R3-rerank-0.6b-GGUF: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 LeadingPoint/R3-rerank-0.6b-GGUF:# Run inference directly in the terminal:
./llama-cli -hf LeadingPoint/R3-rerank-0.6b-GGUF: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 LeadingPoint/R3-rerank-0.6b-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf LeadingPoint/R3-rerank-0.6b-GGUF:Use Docker
docker model run hf.co/LeadingPoint/R3-rerank-0.6b-GGUF:Quick Links
R3-rerank-0.6b GGUF
GGUF quantizations of tencent/R3-rerank-0.6b.
Original Model
https://huggingface.co/tencent/R3-rerank-0.6b
All credit for the original authors.
Files
| File | Description |
|---|---|
| R3-rerank-0.6b-Q4_K_M.gguf | Q4_K_M quantization |
Conversion
Converted using the latest llama.cpp tools.
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Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf LeadingPoint/R3-rerank-0.6b-GGUF:# Run inference directly in the terminal: llama cli -hf LeadingPoint/R3-rerank-0.6b-GGUF: