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BERT is a method of pre-training language representations, meaning that we train a general-purpose "language understanding" model on a large text corpus (like ...

10.01.2021 · An Unsupervised Sentence Embedding Method by Mutual Information Maximization (EMNLP2020) - GitHub - yanzhangnlp/IS-BERT: An Unsupervised Sentence Embedding Method by Mutual Information Maximization (EMNLP2020)

Getting Started with Google BERT, published by Packt - GitHub - PacktPublishing/Getting-Started-with-Google-BERT: Getting Started with Google BERT, ...

from transformers import AutoTokenizer, AutoModel >>> tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased") >>> model ...

11.03.2020 · BERT-Base, Chinese : Chinese Simplified and Traditional, 12-layer, 768-hidden, 12-heads, 110M parameters. Each .zip file contains three items: A TensorFlow checkpoint ( bert_model.ckpt) containing the pre-trained weights (which is actually 3 files). A vocab file ( vocab.txt) to map WordPiece to word id.

Contribute to sf-wa-326/phrase-bert-topic-model development by creating an account on GitHub.

TensorFlow code and pre-trained models for BERT.

Pre-Trained Models for ToD-BERT. Contribute to jasonwu0731/ToD-BERT development by creating an account on GitHub.

Implementation of BERT that could load official pre-trained models for feature extraction and prediction - GitHub - CyberZHG/keras-bert: Implementation of ...

Fast-Bert is the deep learning library that allows developers and data scientists to train and deploy BERT and XLNet based models for natural language ...

08.01.2022 · class BERT. BERT(args) :: Module. Base class for all neural network modules. Your models should also subclass this class. Modules can also contain other Modules, allowing to nest them in a tree structure.

Pre-trained Nordic models for BERT. Contribute to certainlyio/nordic_bert development by creating an account on GitHub.

README.md ... Running Google BERT with Multilingual (104 languages) pretrained neural net locally or via Google Colab. Google BERT official page: https://github.

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