Instructions to use sumitkalamkar/mistral-7b-medical-qa-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sumitkalamkar/mistral-7b-medical-qa-qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "sumitkalamkar/mistral-7b-medical-qa-qlora") - Notebooks
- Google Colab
- Kaggle
Mistral-7B Medical QA — QLoRA Fine-tuned
Author: Sumit Pandurang Kalamkar
Platform: Google Colab (Tesla T4 16GB)
Date: March 2026
Model Description
Mistral-7B-v0.1 fine-tuned on PubMed QA (pqa_labeled) using QLoRA for biomedical question answering. Trained on 630 samples using only 1.2% of total parameters on a single free T4 GPU.
Results
| Model | ROUGE-1 | ROUGE-2 | ROUGE-L |
|---|---|---|---|
| Mistral-7B (zero-shot) | 0.2138 | 0.0707 | 0.1532 |
| This model (QLoRA) | 0.3445 | 0.1249 | 0.2288 |
| Improvement | +61% | +76% | +49% |
Training Details
| Property | Value |
|---|---|
| Base Model | Mistral-7B-v0.1 |
| Dataset | PubMed QA (pqa_labeled) |
| Train Samples | 630 |
| Test Samples | 70 |
| LoRA Rank | 8 |
| LoRA Alpha | 16 |
| Target Modules | q_proj, v_proj |
| Trainable Params | ~1.2% |
| Quantization | 4-bit NF4 |
| Learning Rate | 2e-4 |
| Total Steps | 600 |
| Final Loss | 1.043 |
| GPU | Tesla T4 16GB |
| Training Time | ~3.86 hours |
Sample Outputs
Q: What are the symptoms of Type 2 diabetes?
The symptoms of type 2 diabetes include increased thirst, increased urination, increased hunger, weight loss, blurred vision, and fatigue. These symptoms occur because the body's cells are starved of glucose.
Q: How does insulin work?
Insulin is a hormone produced by beta cells in the pancreas. It helps cells take in glucose from the blood as fuel. When cells don't respond properly, glucose stays in the blood — this is called insulin resistance.
Q: What causes high blood pressure?
High blood pressure has many causes including narrowed arteries, kidney problems, being overweight, and excess salt in the diet.
How to Use
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
tokenizer = AutoTokenizer.from_pretrained(
"sumitkalamkar/mistral-7b-medical-qa-qlora"
)
model = AutoModelForCausalLM.from_pretrained(
"mistralai/Mistral-7B-v0.1",
torch_dtype=torch.bfloat16,
device_map="auto"
)
model = PeftModel.from_pretrained(
model,
"sumitkalamkar/mistral-7b-medical-qa-qlora"
)
def ask(question):
prompt = f"<s>[INST] You are an expert medical AI assistant. Question: {question} [/INST] Answer:"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens=200,
do_sample=False,
pad_token_id=tokenizer.eos_token_id
)
return tokenizer.decode(
outputs[0][inputs['input_ids'].shape[1]:],
skip_special_tokens=True
).strip()
print(ask("What are the symptoms of Type 2 diabetes?"))
References
- Dettmers et al. (2023). QLoRA. arXiv:2305.14314
- Hu et al. (2021). LoRA. arXiv:2106.09685
- Jin et al. (2019). PubMedQA. EMNLP 2019
- Jiang et al. (2023). Mistral 7B. arXiv:2310.06825
Links
- GitHub: https://github.com/Sumitkalamkar/mistral-7b-medical-qa-qlora
- Research Report: See RESEARCH_REPORT.md in Files tab
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Model tree for sumitkalamkar/mistral-7b-medical-qa-qlora
Base model
mistralai/Mistral-7B-v0.1