🚀 CheXagent
CheXagent是一款用于胸部X光解释的基础模型,它为胸部X光的解读提供了有效的解决方案,具有重要的医学应用价值。
🚀 快速开始
模型发布信息
代码示例
import io
import requests
import torch
from PIL import Image
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "StanfordAIMI/CheXagent-2-3b"
dtype = torch.bfloat16
device = "cuda"
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", trust_remote_code=True)
model = model.to(dtype)
model.eval()
query = tokenizer.from_list_format([*[{'image': path} for path in paths], {'text': prompt}])
conv = [{"from": "system", "value": "You are a helpful assistant."}, {"from": "human", "value": query}]
input_ids = tokenizer.apply_chat_template(conv, add_generation_prompt=True, return_tensors="pt")
output = model.generate(
input_ids.to(device), do_sample=False, num_beams=1, temperature=1., top_p=1., use_cache=True,
max_new_tokens=512
)[0]
response = tokenizer.decode(output[input_ids.size(1):-1])
📚 详细文档
✏️ 引用
@article{chexagent-2024,
title={CheXagent: Towards a Foundation Model for Chest X-Ray Interpretation},
author={Chen, Zhihong and Varma, Maya and Delbrouck, Jean-Benoit and Paschali, Magdalini and Blankemeier, Louis and Veen, Dave Van and Valanarasu, Jeya Maria Jose and Youssef, Alaa and Cohen, Joseph Paul and Reis, Eduardo Pontes and Tsai, Emily B. and Johnston, Andrew and Olsen, Cameron and Abraham, Tanishq Mathew and Gatidis, Sergios and Chaudhari, Akshay S and Langlotz, Curtis},
journal={arXiv preprint arXiv:2401.12208},
url={https://arxiv.org/abs/2401.12208},
year={2024}
}
📄 许可证
本项目采用 cc-by-nc-4.0
许可证。