vilyalabs-med

This model is a fine-tuned version of LiquidAI/LFM2.5-230M optimized for medical chat and consultation.

It was trained using Quantization-Aware Training (QAT) for INT4 weight-only quantization via torchao, combined with LoRA adapters to maintain high reasoning quality while being extremely lightweight.

Model Details

• Base Model: LiquidAI/LFM2.5-230M
• Fine-tuning Method: LoRA + INT4 QAT (Weight-only)
• LoRA Config: rank=16, alpha=32, target_modules=all-linear
• Quantization: INT4 Weight-Only (Group size 128)
• Training Precision: FP16

Training Data

The model was trained on a curated mixture of:

1. ruslanmv/ai-medical-chatbot
2. lavita/ChatDoctor-HealthCareMagic-100k

Intended Use

• Medical information retrieval
• Patient-Doctor dialogue simulation
• Health-related assistant tasks

How to use

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("micymike/vilyalabs-med", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("micymike/vilyalabs-med")