如何从Pytorch中的预训练模型加载保存的令牌生成器 [英] How to load the saved tokenizer from pretrained model in Pytorch
问题描述
我使用 Huggingface Transformer 在 Pytorch 中微调了一个预训练的 BERT 模型.所有训练/验证都是在云中的GPU上完成的.
I fine-tuned a pretrained BERT model in Pytorch using huggingface transformer. All the training/validation is done on a GPU in cloud.
在培训结束时,我将模型和令牌生成器保存如下:
At the end of the training, I save the model and tokenizer like below:
best_model.save_pretrained('./saved_model/')
tokenizer.save_pretrained('./saved_model/')
这将在 saved_model
目录中创建以下文件:
This creates below files in the saved_model
directory:
config.json
added_token.json
special_tokens_map.json
tokenizer_config.json
vocab.txt
pytorch_model.bin
现在,我在计算机上下载了 saved_model
目录,并希望加载模型和令牌生成器.我可以像下面那样加载模型
Now, I download the saved_model
directory in my computer and want to load the model and tokenizer. I can load the model like below
model = torch.load('./saved_model/pytorch_model.bin',map_location = torch.device('cpu'))
但是如何加载令牌生成器?我是pytorch的新手,不确定,因为有多个文件.可能我没有以正确的方式保存模型?
But how do I load the tokenizer? I am new to pytorch and not sure because there are multiple files. Probably I am not saving the model in the right way?
请提出建议.
推荐答案
如果您查看语法,则它是您应该传递的经过预先训练的模型的目录.因此,加载令牌生成器的正确方法必须是:
If you look at the syntax, it is the directory of the pre-trained model that you are supposed to pass. Hence, the correct way to load tokenizer must be:
tokenizer = BertTokenizer.from_pretrained(<包含预训练模型/tokenizer的目录的路径>)
在您的情况下:
tokenizer = BertTokenizer.from_pretrained('./saved_model/')
./saved_model
这是您将保存预训练的模型和令牌生成器的目录.
./saved_model
here is the directory where you'll be saving your pretrained model and tokenizer.
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