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---
license: apache-2.0
datasets:
- medalpaca/medical_meadow_wikidoc_patient_information
pipeline_tag: text-generation
---
# llama-2-7b-chat-MEDS-12
This is a `llama-2-7b-chat-hf` model fine-tuned using QLoRA (4-bit precision) on the [`s200862/medical_qa_meds`](https://huggingface.co/datasets/s200862/medical_qa_meds) dataset. This is an adapted version of the [`medalpaca/medical_meadow_wikidoc_patient_information`](https://huggingface.co/datasets/medalpaca/medical_meadow_wikidoc_patient_information) dataset to match llama-2's instruction format.
## 🔧 Training
It was trained on-premise in a jupyter notebook using an Nvidia RTX A4000 GPU with 16GB of VRAM and 16 GB of system RAM.
## 💻 Usage
It is intended to give answers to medical questions.
``` python
# pip install transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "s200862/llama-2-7b-chat-MEDS-12"
prompt = "What causes Allergy?"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
sequences = pipeline(
f'<s>[INST] {prompt} [/INST]',
do_sample=True,
top_k=10,
num_return_sequences=1,
eos_token_id=tokenizer.eos_token_id,
max_length=200,
)
for seq in sequences:
print(f"Result: {seq['generated_text']}")
``` |