This is a highly specialized, locally fine-tuned LoRA adapter for the Qwen2.5-3B model, designed specifically for clinical cardiology diagnostics. It was trained to act as a domain expert in a Multi-LoRA routing system.

Developed by: Hriday75
Model type: LoRA Adapter (PEFT)
Language: English
Finetuned from base model: unsloth/Qwen2.5-3B-bnb-4bit
Training Stage: Phase 1 (Continued Pre-Training on Domain Knowledge)

Uses

This model is intended to be used as a dynamically loaded adapter. When attached to the base Qwen2.5-3B model, it acts as a highly technical cardiology expert.

Training Details

Training Data

This adapter was trained on high-quality, unstructured cardiology datasets sourced from PubMed (Scientific Literature) and filtered clinical notes from MIMIC-IV to learn dense medical terminology, hemodynamics, and EKG interpretation.

Training Procedure

Trained using unsloth for high-efficiency 4-bit LoRA fine-tuning.

How to Get Started with the Model

python

from peft import PeftModel
from transformers import AutoModelForCausalLM

# 1. Load the base model
base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-3B-bnb-4bit")

# 2. Attach this Cardiology Adapter
model = PeftModel.from_pretrained(base_model, "Hriday75/qwen2.5-3b-cardiology-lora")