BART is a transformer model that combines a bidirectional encoder similar to BERT with an autoregressive decoder akin to GPT. It is trained using two main techniques: (1) corrupting text with a chosen noising function, and (2) training a model to reconstruct the original text. ...
问在python中应用预先训练好的facebook/bart-large-cnn进行文本摘要EN我所处的情况是，我正在使用huggingf...
Model Cards:@julien-c Summarization:@sshleifer examples/distillation:@VictorSanh Bart:@sshleifer documentation:@sgugger --> Information I am using facebook/bart-large-cnn summarization model as mentioned in hugging face website using transformers: ...
f bart-large-cnnBeta Summarization•facebook @cf/facebook/bart-large-cnn BART is a transformer encoder-encoder (seq2seq) model with a bidirectional (BERT-like) encoder and an autoregressive (GPT-like) decoder. You can use this model for text summarization. ...
文本摘要提取的主流算法主要有以下几种：基于统计的方法：这种方法使用统计模型来分析文本，然后提取关键...
DATASETS cnn-model-bart-large-models-r2 zuco-data-set-all-4-v2 Output cnn model bart large models r2 Language Python License This Notebook has been released under the Apache 2.0 open source license. Continue exploring Input2 files arrow_right_alt Output0 files arrow_right_alt Logs4.2 second ...
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