transformers.js/pr_1649/en/api/pipelines.md

pipelines

Pipelines provide a high-level, easy to use, API for running machine learning models.

Example: Instantiate pipeline using the pipeline function.

import { pipeline } from '@huggingface/transformers';

const classifier = await pipeline('sentiment-analysis');
const output = await classifier('I love transformers!');
// [{'label': 'POSITIVE', 'score': 0.999817686}]

• pipelines
  • static
    • .pipeline(task, [model], [options]) ⇒ Promise.<AllTasks>
      • ~files_loading : FilesLoadingMap
      • ~metadata : Array.<{exists: boolean, size: number, contentType: string, fromCache: boolean}>
  • inner
    • ~AllTasks : string

---

pipelines.pipeline(task, [model], [options]) ⇒ Promise.<AllTasks>

Utility factory method to build a Pipeline object.

Kind: static method of pipelines
Returns: Promise.<AllTasks> - A Pipeline object for the specified task.
Throws:

• Error If an unsupported pipeline is requested.

  ParamTypeDefaultDescription
  

  taskTThe task defining which pipeline will be returned. Currently accepted tasks are:

"audio-classification": will return a AudioClassificationPipeline. "automatic-speech-recognition": will return a AutomaticSpeechRecognitionPipeline. "background-removal": will return a BackgroundRemovalPipeline. "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. "object-detection": will return a ObjectDetectionPipeline. "question-answering": will return a QuestionAnsweringPipeline. "summarization": will return a SummarizationPipeline. "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. "zero-shot-classification": will return a ZeroShotClassificationPipeline. "zero-shot-audio-classification": will return a ZeroShotAudioClassificationPipeline. "zero-shot-image-classification": will return a ZeroShotImageClassificationPipeline. "zero-shot-object-detection": will return a ZeroShotObjectDetectionPipeline.

[model]stringnullThe name of the pre-trained model to use. If not specified, the default model for the task will be used.


[options]PretrainedModelOptionsOptional parameters for the pipeline.

  

• .pipeline(task, [model], [options]) ⇒ Promise.<AllTasks>
  • ~files_loading : FilesLoadingMap
  • ~metadata : Array.<{exists: boolean, size: number, contentType: string, fromCache: boolean}>

---

pipeline~files_loading : FilesLoadingMap

Kind: inner property of pipeline

---

pipeline~metadata : Array.<{exists: boolean, size: number, contentType: string, fromCache: boolean}>

Kind: inner constant of pipeline

---

pipelines~AllTasks : string

All possible pipeline types.

Kind: inner typedef of pipelines

---