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AdaptLLM-medical
Bhu1Krishna/AdaptLLM-medical
AdaptLLM-medical is a text generation model from Bhu1Krishna. Use it when you need the model to write or continue text. The card lists the license as mit.
A QLoRA fine-tuned version of Gemma 3 4B on the ChatDoctor-HealthCareMagic dataset for medical Q&A.
Access
Public
Updated May 19, 2026
Repo size
57.2 MB
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Repo makeup
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.json33.4 MB · 58%
At a glance
- Task
- Text Generation
- License
- mit
- Access
- Public
- Created
- May 19, 2026
- Updated
- May 19, 2026
- SHA
- 82111366
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Base models
Model card
From the Hugging Face model README
AdaptLLM Medical — Fine-tuned Gemma 3 4B
A QLoRA fine-tuned version of Gemma 3 4B on the ChatDoctor-HealthCareMagic dataset for medical Q&A.
Model Details
- Base model: google/gemma-3-4b-it
- Fine-tuning method: QLoRA (LoRA rank 16, alpha 32)
- Dataset: ChatDoctor-HealthCareMagic-100k (500 rows)
- Training: 3 epochs, ~21 minutes on RTX 4060 8GB
- Trainable parameters: 11.8M out of 4.3B (0.27%)
Training Results
| Epoch | Loss | Token Accuracy |
|---|---|---|
| 1 | 2.402 | 0.49 |
| 2 | 2.300 | 0.51 |
| 3 | 2.261 | 0.52 |
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base = AutoModelForCausalLM.from_pretrained("google/gemma-3-4b-it")
model = PeftModel.from_pretrained(base, "BhuvanKrishna12/adaptllm-medical")
Example
Input: I have been taking metformin and recently started ciprofloxacin. I am experiencing hypoglycemia episodes.
Output: Ciprofloxacin is a fluoroquinolone antibiotic which can affect blood glucose levels when combined with metformin. You should consult your doctor about switching to a different antibiotic.
Disclaimer
This model is for research and educational purposes only. Not intended for actual medical diagnosis or treatment.
Built with
AdaptLLM — a local LLM fine-tuning pipeline
- Task
- Text Generation
- License
- mit
- Languages
- en
- Created
- May 19, 2026
- Updated
- May 19, 2026