MODEL_TYPE_PRE_TRAINED_SUMMARIZATION = 'PRE_TRAINED_SUMMARIZATION' MODEL_TYPE_PRE_TRAINED_TEXT_CLASSIFICATION = 'PRE_TRAINED_TEXT_CLASSIFICATION'MODEL_TYPE_PRE_TRAINED_TRANSLATION = 'PRE_TRAINED_TRANSLATION' MODEL_TYPE_PRE_TRAINED_UNIVERSAL = 'PRE_TRAINED_UNIVERSAL' MODEL_TY...
Text Summarization 综述 ABS 和 ABS+ [Rush, 2015] A Neural Attention Model for Abstractive Sentence Summarization 这篇 facebook 的论文是用神经网络来做生成式摘要的开山之作,后续的论文基本都会引用。而且在 github 上有开源的代码放出来,可以参考 facebook/NAMAS. 模型的主要结构见下图(a),即左边的那...
model = BertForSequenceClassification.from_pretrained(model_name) # 这里我们使用BERT进行分类任务的模型,但实际上你可以使用其他任何BERT模型 # 定义文本摘要的pipeline summarizer = pipeline("summarization", model=model, tokenizer=tokenizer) # 输入要摘要的文本 text = "这是一段非常长的文本,需要被摘要成简...
The Megatron-Turing NLG-530B model is a generative language model developed by NVIDIA that utilizes DeepSpeed and Megatron to train the largest and most powerful model of its kind. It has over 530 billion parameters, making it capable of generating high-quality text for a variety of tasks such...
To enhance the generalization ability of PanGu- α \alpha , we collect 1.1TB high-quality Chinese data from a wide range of domains to pretrain the model. We empirically test the generation ability of PanGu- α \alpha in various scenarios including text summarization, question answering, ...
This dataset has been tested using BART, Text-to-Text transformer (T5), model generated using transfer learning over T5, and an encoder-decoder based model developed from scratch. The results show that T5 gives better result than other three models used for testing....
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Latent Dirichlet Allocation (LDA) Algorithm, Neural Topic Model (NTM) Algorithm Assign pre-defined categories to documents in a corpus: categorize books in a library into academic disciplines Textual analysis Text classification Text BlazingText algorithm, Text Classification - TensorFlow Convert text ...
Inspired by BERT, we propose Med-BERT, which adapts the BERT framework originally developed for the text domain to the structured EHR domain. Med-BERT is a contextualized embedding model pretrained on a structured EHR dataset of 28,490,650 patients. Fine-tuning experiments showed that Med-BERT ...
💻 Source Code Summarization (Bleu): Language / ModelPythonSQLC# CodeTrans-ST-Small8.4517.5519.74 CodeTrans-ST-Base9.1215.0018.65 CodeTrans-TF-Small10.0617.7120.40 CodeTrans-TF-Base10.9417.6621.12 CodeTrans-TF-Large12.4118.4021.43 CodeTrans-MT-Small13.1119.1522.39 ...