How to use from
Pi
Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf simonguest/Qwen3-1.7B-code-explainer:F16
Configure the model in Pi
# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "simonguest/Qwen3-1.7B-code-explainer:F16"
        }
      ]
    }
  }
}
Run Pi
# Start Pi in your project directory:
pi
Quick Links

Qwen3-1.7B-code-explainer

Model Description

Fine-tuned from Qwen/Qwen3-1.7B using QLoRA (4-bit) with supervised fine-tuning.

Training Details

  • Dataset: simonguest/test-dataset
  • LoRA rank: 16, alpha: 32
  • Epochs: 3, Learning rate: 0.0002

Intended Use

This model is a test model used for the CS-394/594 class at DigiPen.

The model is designed to provide a summary explanation of a snippet of Python code, to be used in an IDE. This model takes a snippet of code (passed as the user prompt) and returns a two paragraph explanation of what the code does, including an analogy that helps students better understand how the code functions.

Limitations

This model is a single-turn model and has not been trained on support long, multi-turn conversations.

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