mlwithme/BertWithPretrained
A PyTorch implementation of BERT from scratch with fine-tuning examples for text classification, question answering, NER, and pre-training tasks.
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This project provides a从头实现 implementation of the BERT model architecture and demonstrates its application on common NLP downstream tasks. It includes implementations for Chinese text classification, English entailment (MNLI), multiple choice (SWAG), question answering (SQuAD), and named entity recognition. The repository also contains a pre-training module that trains BERT from scratch using Next Sentence Prediction and Masked Language Model objectives.
Frequently asked
- What is mlwithme/BertWithPretrained?
- A PyTorch implementation of BERT from scratch with fine-tuning examples for text classification, question answering, NER, and pre-training tasks.
- Is BertWithPretrained open source?
- Yes — mlwithme/BertWithPretrained is an open-source project tracked on heatdrop.
- What language is BertWithPretrained written in?
- mlwithme/BertWithPretrained is primarily written in Python.
- How popular is BertWithPretrained?
- mlwithme/BertWithPretrained has 604 stars on GitHub.
- Where can I find BertWithPretrained?
- mlwithme/BertWithPretrained is on GitHub at https://github.com/mlwithme/BertWithPretrained.