How to use from
Unsloth Studio
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Khalidahmad01/cortex-copilot-lora to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Khalidahmad01/cortex-copilot-lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Khalidahmad01/cortex-copilot-lora to start chatting
Load model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="Khalidahmad01/cortex-copilot-lora",
    max_seq_length=2048,
)
Quick Links

Cortex Copilot LoRA Adapter

Overview

This repository contains the LoRA adapter developed for the Cortex Copilot Engineering Challenge.

The adapter fine-tunes Qwen2.5-3B-Instruct using QLoRA to improve responses for industrial energy management, electrical engineering concepts, Indian electricity tariff logic, and Cortex-specific metrics.


Base Model

Qwen/Qwen2.5-3B-Instruct


Fine-Tuning Method

  • Framework: Unsloth
  • Method: QLoRA
  • PEFT (Parameter-Efficient Fine-Tuning)

Dataset

The model was fine-tuned on 399 instruction-response pairs covering:

  • Electrical Engineering Concepts
  • Indian Industrial Tariff Rules
  • Cortex Metric Explanations
  • Energy Optimization
  • Refusal Behaviour
  • Tenant Isolation
  • Prompt Injection Resistance

Training Configuration

Parameter Value
Epochs 3
Batch Size 2
Gradient Accumulation 4
Learning Rate 2e-4
Max Sequence Length 2048
GPU Tesla T4

Files

  • adapter_model.safetensors
  • adapter_config.json
  • tokenizer.json
  • tokenizer_config.json
  • chat_template.jinja

Intended Use

This adapter is intended for educational purposes as part of the Cortex Copilot Engineering Challenge.

It specializes the base model for industrial energy management while relying on external telemetry data for real-time information.


Author

Khalid Ahmad Raza

B.Tech Computer Engineering

National Institute of Technology Kurukshetra

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