Leveraging BERT and c-TF-IDF to create easily interpretable topics. - GitHub - MaartenGr/BERTopic: Leveraging BERT and c-TF-IDF to create easily interpretable topics.
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org/abs/1706.03762 Also see: https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/models/transformer.py Args: input_tensor: float Tensor of shape [batch_size, seq_length, hidden_size]. attention_mask: (optional) int32 Tensor of shape [batch_size, seq_length, seq_length],...
官方代码和预训练模型 Github: https://github.com/google-research/bert Google AI Blog:Open Sourcing BERT: State-of-the-Art Pre-training for Natural Language Processing 第三方代码 pytorch-pretrained-BERTGoogle官方推荐的PyTorch BERB版本实现,可加载Google预训练的模型:PyTorch version of Google AI’s BERT...
# https://github.com/pytorch/pytorch/blob/master/torch/nn/modules/transformer.py # 412行 self.norm1 = LayerNorm(d_model, eps=layer_norm_eps, **factory_kwargs) # huggingface bert_model # https://github.com/huggingface/transformers...
https://github.com/google-research/bert BERT,全称是BidirectionalEncoderRepresentations fromTransformers,是一种预训练语言表示的新方法。 新智元近期对BERT模型作了详细的报道和专家解读: NLP历史突破!谷歌BERT模型狂破11项纪录,全面超越人类! 狂破11项记录,谷歌年度最强NLP论文到底强在哪里?
答:bert源码后面会慢慢展开,transformer推荐“The Annotated Transformer”。 八、Refs BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding https://github.com/huggingface/transformers https://github.com/google-research/bert
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GitHub链接:github.com/harvardnlp/a Post Scriptum 虽然在Transformer文章中提出了一种自然语言翻译的模型,很多文章把这个模型称为Transformer。但我们还是倾向于将文章中利用Self-Attention的Encoder或Decoder的子结构称为Transformer。文中和源码中还包...
参考实现 https://github.com/Qdriving/Bert4Rec_Paddle2.0 PaddlePaddle官方的Transformer https://github.com/PaddlePaddle/Paddle/blob/2a7c2cf8f32541f3c7691b852bd4a8fe48505294/python/paddle/fluid/tests/unittests/dygraph_to_static/transformer_dygraph_model.py#L250最后...