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 Ajay-21/bling-phi-2-v0-GGUF:
# Run inference directly in the terminal:
llama-cli -hf Ajay-21/bling-phi-2-v0-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Ajay-21/bling-phi-2-v0-GGUF:
# Run inference directly in the terminal:
llama-cli -hf Ajay-21/bling-phi-2-v0-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 Ajay-21/bling-phi-2-v0-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf Ajay-21/bling-phi-2-v0-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 Ajay-21/bling-phi-2-v0-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Ajay-21/bling-phi-2-v0-GGUF:
Use Docker
docker model run hf.co/Ajay-21/bling-phi-2-v0-GGUF:
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Model Card for Model ID

This is quantized 4 bit, 5 bit, 8 bit and fp16 model versions of the bling-phi-2-v0 by llmware. Quantized models are in gguf format and done using llama.cpp

Model Description

For more info about prompt template refer the original model repo.

Original Model Details:

Creator: llmware

Link: https://huggingface.co/llmware/bling-phi-2-v0

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GGUF
Model size
3B params
Architecture
phi2
Hardware compatibility
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