Bert_classifier 这是一个用于问题分类的模型，配合Fourth Dimension的一些版本进行使用
以下为源模型bert-base-chinese的readme.md
Bert-base-chinese Table of Contents Model Details Uses Risks, Limitations and Biases Training Evaluation How to Get Started With the Model Model Details Model Description This model has been pre-trained for Chinese, training and random input masking has been applied independently to word pieces (as in the original BERT paper).
Developed by: HuggingFace team Model Type: Fill-Mask Language(s): Chinese License: [More Information needed] Parent Model: See the BERT base uncased model for more information about the BERT base model. Model Sources Paper: BERT Uses Direct Use This model can be used for masked language modeling
Risks, Limitations and Biases CONTENT WARNING: Readers should be aware this section contains content that is disturbing, offensive, and can propagate historical and current stereotypes.
Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)).
Training Training Procedure typevocabsize: 2 vocabsize: 21128 numhidden_layers: 12 Training Data [More Information Needed]
Evaluation Results [More Information Needed]
How to Get Started With the Model from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("bert-base-chinese")
model = AutoModelForMaskedLM.from_pretrained("bert-base-chinese")
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