bert4torch_config

bert4torch配套config

• bert4torch加载模型时候可以在线加载，无需下载文件
• Github主页
• 预训练模型支持多种代码加载方式

from bert4torch.models import build_transformer_model

# 1. 仅指定config_path: 从头初始化模型结构, 不加载预训练模型
model = build_transformer_model('./model/bert4torch_config.json')

# 2. 仅指定checkpoint_path: 
## 2.1 文件夹路径: 自动寻找路径下的*.bin/*.safetensors权重文件 + bert4torch_config.json/config.json文件
model = build_transformer_model(checkpoint_path='./model')

## 2.2 文件路径/列表: 文件路径即权重路径/列表, config会从同级目录下寻找
model = build_transformer_model(checkpoint_path='./pytorch_model.bin')

## 2.3 model_name: hf上预训练权重名称, 会自动下载hf权重以及bert4torch_config.json文件
model = build_transformer_model(checkpoint_path='bert-base-chinese')

# 3. 同时指定config_path和checkpoint_path(本地路径名或model_name排列组合): 
config_path = './model/bert4torch_config.json'  # 或'bert-base-chinese'
checkpoint_path = './model/pytorch_model.bin'  # 或'bert-base-chinese'
model = build_transformer_model(config_path, checkpoint_path)