Instructions to use quincyqiang/nezha-cn-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use quincyqiang/nezha-cn-base with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("quincyqiang/nezha-cn-base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
NeZha-Pytorch
pytorch版NEZHA,适配transformers
安装
pip install git+https://github.com/yanqiangmiffy/Nezha-Pytorch.git
权重下载地址
https://github.com/lonePatient/NeZha_Chinese_PyTorch
torch使用样例
import torch
from transformers import BertTokenizer
from nezha import NeZhaModel, NeZhaConfig
text = "今天[MASK]很好,我[MASK]去公园玩。"
tokenizer = BertTokenizer.from_pretrained(
"quincyqiang/nezha-cn-base"
)
model = NeZhaModel.from_pretrained(
"quincyqiang/nezha-cn-base"
)
config = NeZhaConfig.from_pretrained(
"quincyqiang/nezha-cn-base"
)
model.eval()
inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
outputs = model(**inputs)
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