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1import torch
2import pandas as pd
3from transformers import AutoTokenizer, AutoModelForCausalLM
4
5model_path = "medicalai/MedFound-Llama3-8B-finetuned"
6tokenizer = AutoTokenizer.from_pretrained(model_path)
7model = AutoModelForCausalLM.from_pretrained(model_path, device_map="auto")
8data = pd.read_json('data/test.zip', lines=True).iloc[1]
9
10input_text = f"### User:{data['context']}\n\nPlease provide a detailed and comprehensive diagnostic analysis of this medical record.\n### Assistant:"
11input_ids = tokenizer.encode(input_text, return_tensors="pt", add_special_tokens=False)
12output_ids = model.generate(input_ids, max_new_tokens=200, temperature=0.7, do_sample=True).to(model.device)
13generated_text = tokenizer.decode(output_ids[0,len(input_ids[0]):], skip_special_tokens=True)
14print("Generated Output:\n", generated_text)