Upload README.md

README.md

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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']}")
+```