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 Colby/starcoder-7b-agent-0.5-gguf:
# Run inference directly in the terminal:
llama cli -hf Colby/starcoder-7b-agent-0.5-gguf:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Colby/starcoder-7b-agent-0.5-gguf:
# Run inference directly in the terminal:
llama cli -hf Colby/starcoder-7b-agent-0.5-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 Colby/starcoder-7b-agent-0.5-gguf:
# Run inference directly in the terminal:
./llama-cli -hf Colby/starcoder-7b-agent-0.5-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 Colby/starcoder-7b-agent-0.5-gguf:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Colby/starcoder-7b-agent-0.5-gguf:
Use Docker
docker model run hf.co/Colby/starcoder-7b-agent-0.5-gguf:
Quick Links

starcoder-7b-agent-0.5-gguf

GGUF conversion of Colby/starcoder-7b-agent-0.5, fine-tuned from Colby/starcoder-7b-agent-0.3-merged.

v0.5 adds 6 special tokens (<tool_call>, </tool_call>, <tool_response>, </tool_response>, <think>, </think>) with dedicated embeddings (vocab 49162).

Chat format: StarCoderChat with <think>...</think> and <tool_call>/<tool_response> blocks.

Quantizations

File Format Size
starcoder-7b-agent-0.5-f16.gguf FP16 ~14 GB
starcoder-7b-agent-0.5-q8_0.gguf Q8_0 ~7 GB
starcoder-7b-agent-0.5-q5_k_m.gguf Q5_K_M ~5 GB
starcoder-7b-agent-0.5-q4_k_m.gguf Q4_K_M ~4 GB
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GGUF
Model size
7B params
Architecture
starcoder
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