README.md

metadata

license: mit

ChiMed-GPT

ChiMed-GPT is a Chinese medical large language model (LLM) that is built by continually training Ziya-v2 on Chinese medical data, where pre-training, supervised fine-tuning (SFT), and reinforcement learning from human feedback (RLHF) are performed.

More information about the model is coming soon.

Citation

If you use or extend our work, please cite the following paper:

@article{USTC-ChiMed-GPT,
  title="{ChiMed-GPT: A Chinese Medical Large Language Model with Full Training Regime and Better Alignment to Human Preferences}",
  author={Yuanhe Tian, Ruyi Gan, Yan Song, Jiaxing Zhang, Yongdong Zhang},
  journal={arXiv preprint arXiv:0000.00000},
  year={2023},
}

Usage

from transformers import AutoTokenizer
from transformers import LlamaForCausalLM
import torch

query="[human]:感冒怎么处理？\n[bot]:"
model = LlamaForCausalLM.from_pretrained('SYNLP/ChiMed-GPT-1.0', torch_dtype=torch.float16, device_map="auto").eval()
tokenizer = AutoTokenizer.from_pretrained(ckpt)
input_ids = tokenizer(query, return_tensors="pt").input_ids.to('cuda:0')
generate_ids = model.generate(
            input_ids,
            max_new_tokens=512, 
            do_sample = True, 
            top_p = 0.9)
output = tokenizer.batch_decode(generate_ids)[0]
print(output)