README.md

metadata

title: SLM Function Calling
emoji: 🚗
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
license: mit
tags:
  - function-calling
  - gpt2
  - lora
  - car-control
  - nlp

SLM Function Calling - Car Control Demo

Convert natural language commands into structured function calls using a fine-tuned GPT-2 model with LoRA.

Demo

Try commands like:

• "Set the temperature to 22 degrees for the driver"
• "Turn up the heat"
• "Navigate to Central Park"
• "Play jazz music at volume 7"
• "Lock all the doors"

Model Details

Property	Value
Base Model	GPT-2 (124M parameters)
Fine-tuning	LoRA (rank=32, alpha=32)
Training Data	~156K car control command samples
Functions	18 car control functions
Input	Natural language command
Output	Structured function call JSON

Function Categories

The model supports 18 functions across these categories:

• Climate Control: set_temperature, adjust_temperature, set_fan_speed, adjust_fan_speed
• Comfort: adjust_seat, control_window
• Wipers & Defroster: set_wiper_speed, adjust_wiper_speed, activate_defroster
• Engine & Security: start_engine, lock_doors
• Entertainment: play_music
• Navigation: set_navigation_destination
• Lighting: toggle_headlights, control_ambient_lighting
• Driving: set_cruise_control, toggle_sport_mode
• Maintenance: check_battery_health

Output Format

The model generates function calls in this format:

<functioncall> {"name": "function_name", "arguments": "{'param': value}"} <|im_end|>

Training

The model was trained using:

• ChatML format with system/user/assistant messages
• Label masking (loss computed only on assistant response)
• LoRA adapters targeting attention layers (c_attn, c_proj)

Limitations

• Only trained on car control domain
• May produce incorrect outputs for ambiguous or out-of-domain queries
• Best results with clear, specific commands

Links

• GitHub Repository
• Model Weights on HuggingFace