Transformers库中的pipeline模块支持的NLP任务

Transformers库中的pipeline模块支持的NLP任务

Transformers库中的pipeline模块支持以下的NLP任务:

• Text Classification(文本分类):文本分类任务,比如情感分析, toxicity检测等。
• Token Classification(标记分类): 序列标记任务,比如命名实体识别, 部分性提取等。
• Question Answering(问答):question answering任务,可以回答给定问题的答案。
• Fill Mask(填充掩码):使用模型预测被掩码的词语。
• Summarization(文本摘要): 文本摘要任务,可以自动生成文本摘要。
• Translation(翻译):机器翻译任务,可以翻译不同语言。
• Feature Extraction(特征提取):从文本中提取语义特征向量。
• Conversational(对话):用于任务型对话,可以问答。
• Text Generation(文本生成):自动生成文本。
• Sentiment Analysis(情感分析):情感分析,判断文本情感极性。
• Named Entity Recognition (NER)(命名实体识别):命名实体识别,找出文本中实体。
• 等等
  使用pipeline可以便捷地完成这些NLP 下游任务,无需训练模型,通过指定任务类型、模型名称即可使用。它封装了模型和tokenization,可以快速上手NLP项目。

2023年9月，产品 pipeline 的代码，全列表如下，

• "audio-classification": will return a [AudioClassificationPipeline].
• "automatic-speech-recognition": will return a [AutomaticSpeechRecognitionPipeline].
• "conversational": will return a [ConversationalPipeline].
• "depth-estimation": will return a [DepthEstimationPipeline].
• "document-question-answering": will return a [DocumentQuestionAnsweringPipeline].
• "feature-extraction": will return a [FeatureExtractionPipeline].
• "fill-mask": will return a [FillMaskPipeline]:.
• "image-classification": will return a [ImageClassificationPipeline].
• "image-segmentation": will return a [ImageSegmentationPipeline].
• "image-to-text": will return a [ImageToTextPipeline].
• "mask-generation": will return a [MaskGenerationPipeline].
• "object-detection": will return a [ObjectDetectionPipeline].
• "question-answering": will return a [QuestionAnsweringPipeline].
• "summarization": will return a [SummarizationPipeline].
• "table-question-answering": will return a [TableQuestionAnsweringPipeline].
• "text2text-generation": will return a [Text2TextGenerationPipeline].
• "text-classification" (alias "sentiment-analysis" available): will return a
  [TextClassificationPipeline].
• "text-generation": will return a [TextGenerationPipeline]:.
• "token-classification" (alias "ner" available): will return a [TokenClassificationPipeline].
• "translation": will return a [TranslationPipeline].
• "translation_xx_to_yy": will return a [TranslationPipeline].
• "video-classification": will return a [VideoClassificationPipeline].
• "visual-question-answering": will return a [VisualQuestionAnsweringPipeline].
• "zero-shot-classification": will return a [ZeroShotClassificationPipeline].
• "zero-shot-image-classification": will return a [ZeroShotImageClassificationPipeline].
• "zero-shot-audio-classification": will return a [ZeroShotAudioClassificationPipeline].
• "zero-shot-object-detection": will return a [ZeroShotObjectDetectionPipeline].

完结！