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vilyalabs-med
micymike/vilyalabs-med
vilyalabs-med is a machine learning model from micymike. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
This model is a fine-tuned version of LiquidAI/LFM2.5-230M optimized for medical chat and consultation.
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At a glance
- License
- apache-2.0
- Model type
- lfm2
- Access
- Public
- Created
- Jul 20, 2026
- Updated
- Jul 20, 2026
- SHA
- 7b87cd30
Base models
Model card
From the Hugging Face model README
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:
ruslanmv/ai-medical-chatbotlavita/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")
- Type
- lfm2
- License
- apache-2.0
- Languages
- en
- Created
- Jul 20, 2026
- Updated
- Jul 20, 2026