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 Tetsuto/iac-repair-3b-gguf:F16
# Run inference directly in the terminal:
llama-cli -hf Tetsuto/iac-repair-3b-gguf:F16
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Tetsuto/iac-repair-3b-gguf:F16
# Run inference directly in the terminal:
llama-cli -hf Tetsuto/iac-repair-3b-gguf:F16
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 Tetsuto/iac-repair-3b-gguf:F16
# Run inference directly in the terminal:
./llama-cli -hf Tetsuto/iac-repair-3b-gguf:F16
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 Tetsuto/iac-repair-3b-gguf:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Tetsuto/iac-repair-3b-gguf:F16
Use Docker
docker model run hf.co/Tetsuto/iac-repair-3b-gguf:F16
Quick Links

iac-repair-3b-gguf

Fine-tuned Qwen2.5-Coder-3B for Infrastructure-as-Code repair. Use with stackfix.

pass@1: 0.867 on Cloud-Gym benchmark (188 entries, 8 error categories)

Quick Start

pip install cloud-gym[gguf]

python -c "
from huggingface_hub import hf_hub_download
hf_hub_download('Tetsuto/iac-repair-3b-gguf', 'iac-repair-3b-q4.gguf', local_dir='.')
"

stackfix repair broken.tf --backend gguf --model iac-repair-3b-q4.gguf

Requirements

  • Disk: 1.8 GB (Q4) | RAM: ~4 GB | Speed: 49 tok/s (CPU)
  • Best for: CI/CD, pre-commit, servers
  • Runs on Linux, macOS, Windows. No GPU required.

Source

Downloads last month
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GGUF
Model size
3B params
Architecture
qwen2
Hardware compatibility
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16-bit

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