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 snowmead/qwen3-0.6b-rust-sft-GGUF:Q8_0
# Run inference directly in the terminal:
llama-cli -hf snowmead/qwen3-0.6b-rust-sft-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf snowmead/qwen3-0.6b-rust-sft-GGUF:Q8_0
# Run inference directly in the terminal:
llama-cli -hf snowmead/qwen3-0.6b-rust-sft-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 snowmead/qwen3-0.6b-rust-sft-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf snowmead/qwen3-0.6b-rust-sft-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 snowmead/qwen3-0.6b-rust-sft-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf snowmead/qwen3-0.6b-rust-sft-GGUF:Q8_0
Use Docker
docker model run hf.co/snowmead/qwen3-0.6b-rust-sft-GGUF:Q8_0
Quick Links

qwen3-0.6b-rust-sft (GGUF)

This is a GGUF quantized version of snowmead/qwen3-0.6b-rust-sft.

Model Details

Usage

LM Studio

  1. Download qwen3-0.6b-rust-sft-q8_0.gguf
  2. Place in your LM Studio models folder
  3. Load and chat!

llama.cpp

./llama-cli -m qwen3-0.6b-rust-sft-q8_0.gguf -c 2048 -cnv

Training

This model was fine-tuned on the Strandset-Rust-Think dataset for Rust code generation with reasoning capabilities.

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GGUF
Model size
0.6B params
Architecture
qwen3
Hardware compatibility
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8-bit

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