How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Plofski/MyPythonCoder-GGUF:BF16# Run inference directly in the terminal:
llama-cli -hf Plofski/MyPythonCoder-GGUF:BF16Use 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 Plofski/MyPythonCoder-GGUF:BF16# Run inference directly in the terminal:
./llama-cli -hf Plofski/MyPythonCoder-GGUF:BF16Build 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 Plofski/MyPythonCoder-GGUF:BF16# Run inference directly in the terminal:
./build/bin/llama-cli -hf Plofski/MyPythonCoder-GGUF:BF16Use Docker
docker model run hf.co/Plofski/MyPythonCoder-GGUF:BF16Quick Links
training
this model has been trained for 3 epochs (for now) on the Flytech python-codes-25k dataset.
This model is a compact Python code assistant with only 270m parameters designed for:
Assisting with Python scripting and function design
Answering Python-related programming questions
Generating and completing Python code snippets
Offering code explanations and debugging hints
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Model tree for Plofski/MyPythonCoder-GGUF
Base model
google/gemma-3-270m Finetuned
google/gemma-3-270m-it Quantized
unsloth/gemma-3-270m-it-GGUF
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf Plofski/MyPythonCoder-GGUF:BF16# Run inference directly in the terminal: llama-cli -hf Plofski/MyPythonCoder-GGUF:BF16