Class: HfInferenceEndpoint

Hierarchy

• TaskWithNoAccessTokenNoEndpointUrl

  ↳ HfInferenceEndpoint

Constructors

constructor

• new HfInferenceEndpoint(endpointUrl, accessToken?, defaultOptions?): HfInferenceEndpoint

Parameters

Name	Type	Default value
endpointUrl	string	undefined
accessToken	string	""
defaultOptions	Options	{}

Returns

HfInferenceEndpoint

Defined in

inference/src/HfInference.ts:51

Properties

audioClassification

• audioClassification: (args: { data: Blob | ArrayBuffer ; model?: string }, options?: Options) => Promise\<AudioClassificationReturn>

Type declaration

▸ (args, options?): Promise\<AudioClassificationReturn>

Parameters

Name	Type	Description
args	Object	-
args.data	Blob | ArrayBuffer	Binary audio data
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<AudioClassificationReturn>

Defined in

inference/src/tasks/audio/audioClassification.ts:30

---

audioToAudio

• audioToAudio: (args: { data: Blob | ArrayBuffer ; model?: string }, options?: Options) => Promise\<AudioToAudioReturn>

Type declaration

▸ (args, options?): Promise\<AudioToAudioReturn>

Parameters

Name	Type	Description
args	Object	-
args.data	Blob | ArrayBuffer	Binary audio data
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<AudioToAudioReturn>

Defined in

inference/src/tasks/audio/audioToAudio.ts:35

---

automaticSpeechRecognition

• automaticSpeechRecognition: (args: { data: Blob | ArrayBuffer ; model?: string }, options?: Options) => Promise\<AutomaticSpeechRecognitionOutput>

Type declaration

▸ (args, options?): Promise\<AutomaticSpeechRecognitionOutput>

Parameters

Name	Type	Description
args	Object	-
args.data	Blob | ArrayBuffer	Binary audio data
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<AutomaticSpeechRecognitionOutput>

Defined in

inference/src/tasks/audio/automaticSpeechRecognition.ts:23

---

chatCompletion

• chatCompletion: (args: {}, options?: Options) => Promise\<ChatCompletionOutput>

Type declaration

▸ (args, options?): Promise\<ChatCompletionOutput>

Parameters

Name	Type
args	Object
options?	Options

Returns

Promise\<ChatCompletionOutput>

Defined in

inference/src/tasks/nlp/chatCompletion.ts:10

---

chatCompletionStream

• chatCompletionStream: (args: {}, options?: Options) => AsyncGenerator\<ChatCompletionStreamOutput, any, unknown>

Type declaration

▸ (args, options?): AsyncGenerator\<ChatCompletionStreamOutput, any, unknown>

Parameters

Name	Type
args	Object
options?	Options

Returns

AsyncGenerator\<ChatCompletionStreamOutput, any, unknown>

Defined in

inference/src/tasks/nlp/chatCompletionStream.ts:8

---

documentQuestionAnswering

• documentQuestionAnswering: (args: { inputs: { image: Blob | ArrayBuffer ; question: string } ; model?: string }, options?: Options) => Promise\<DocumentQuestionAnsweringOutput>

Type declaration

▸ (args, options?): Promise\<DocumentQuestionAnsweringOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	Object	-
args.inputs.image	Blob | ArrayBuffer	Raw image You can use native File in browsers, or new Blob([buffer]) in node, or for a base64 image new Blob([btoa(base64String)]), or even await (await fetch('...)).blob()
args.inputs.question	string	-
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<DocumentQuestionAnsweringOutput>

Defined in

inference/src/tasks/multimodal/documentQuestionAnswering.ts:42

---

featureExtraction

• featureExtraction: (args: { inputs: string | string[] ; model?: string }, options?: Options) => Promise\<FeatureExtractionOutput>

Type declaration

▸ (args, options?): Promise\<FeatureExtractionOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	string | string[]	The inputs is a string or a list of strings to get the features from. inputs: “That is a happy person”,
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<FeatureExtractionOutput>

Defined in

inference/src/tasks/nlp/featureExtraction.ts:24

---

fillMask

• fillMask: (args: { inputs: string ; model?: string }, options?: Options) => Promise\<FillMaskOutput>

Type declaration

▸ (args, options?): Promise\<FillMaskOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	string	-
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<FillMaskOutput>

Defined in

inference/src/tasks/nlp/fillMask.ts:31

---

imageClassification

• imageClassification: (args: { data: Blob | ArrayBuffer ; model?: string }, options?: Options) => Promise\<ImageClassificationOutput>

Type declaration

▸ (args, options?): Promise\<ImageClassificationOutput>

Parameters

Name	Type	Description
args	Object	-
args.data	Blob | ArrayBuffer	Binary image data
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<ImageClassificationOutput>

Defined in

inference/src/tasks/cv/imageClassification.ts:29

---

imageSegmentation

• imageSegmentation: (args: { data: Blob | ArrayBuffer ; model?: string }, options?: Options) => Promise\<ImageSegmentationOutput>

Type declaration

▸ (args, options?): Promise\<ImageSegmentationOutput>

Parameters

Name	Type	Description
args	Object	-
args.data	Blob | ArrayBuffer	Binary image data
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<ImageSegmentationOutput>

Defined in

inference/src/tasks/cv/imageSegmentation.ts:33

---

imageToImage

• imageToImage: (args: { inputs: Blob | ArrayBuffer ; model?: string ; parameters?: { guess_mode?: boolean ; guidance_scale?: number ; height?: number ; negative_prompt?: string ; num_inference_steps?: number ; prompt?: string ; strength?: number ; width?: number } }, options?: Options) => Promise\<Blob>

Type declaration

▸ (args, options?): Promise\<Blob>

Parameters

Name	Type	Description
args	Object	-
args.inputs	Blob | ArrayBuffer	The initial image condition
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
args.parameters?	Object	-
args.parameters.guess_mode?	boolean	guess_mode only works for ControlNet models, defaults to False In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts. The guidance_scale between 3.0 and 5.0 is recommended.
args.parameters.guidance_scale?	number	Guidance scale: Higher guidance scale encourages to generate images that are closely linked to the text prompt, usually at the expense of lower image quality.
args.parameters.height?	number	The height in pixels of the generated image
args.parameters.negative_prompt?	string	An optional negative prompt for the image generation
args.parameters.num_inference_steps?	number	The number of denoising steps. More denoising steps usually lead to a higher quality image at the expense of slower inference.
args.parameters.prompt?	string	The text prompt to guide the image generation.
args.parameters.strength?	number	strengh param only works for SD img2img and alt diffusion img2img models Conceptually, indicates how much to transform the reference image. Must be between 0 and 1. image will be used as a starting point, adding more noise to it the larger the strength. The number of denoising steps depends on the amount of noise initially added. When strength is 1, added noise will be maximum and the denoising process will run for the full number of iterations specified in num_inference_steps. A value of 1, therefore, essentially ignores image.
args.parameters.width?	number	The width in pixels of the generated image
options?	Options	-

Returns

Promise\<Blob>

Defined in

inference/src/tasks/cv/imageToImage.ts:61

---

imageToText

• imageToText: (args: { data: Blob | ArrayBuffer ; model?: string }, options?: Options) => Promise\<ImageToTextOutput>

Type declaration

▸ (args, options?): Promise\<ImageToTextOutput>

Parameters

Name	Type	Description
args	Object	-
args.data	Blob | ArrayBuffer	Binary image data
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<ImageToTextOutput>

Defined in

inference/src/tasks/cv/imageToText.ts:22

---

objectDetection

• objectDetection: (args: { data: Blob | ArrayBuffer ; model?: string }, options?: Options) => Promise\<ObjectDetectionOutput>

Type declaration

▸ (args, options?): Promise\<ObjectDetectionOutput>

Parameters

Name	Type	Description
args	Object	-
args.data	Blob | ArrayBuffer	Binary image data
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<ObjectDetectionOutput>

Defined in

inference/src/tasks/cv/objectDetection.ts:39

---

questionAnswering

• questionAnswering: (args: { inputs: { context: string ; question: string } ; model?: string }, options?: Options) => Promise\<QuestionAnsweringOutput>

Type declaration

▸ (args, options?): Promise\<QuestionAnsweringOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	Object	-
args.inputs.context	string	-
args.inputs.question	string	-
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<QuestionAnsweringOutput>

Defined in

inference/src/tasks/nlp/questionAnswering.ts:34

---

request

• request: (args: { data: Blob | ArrayBuffer ; model?: string ; parameters?: Record\<string, unknown> } | { inputs: unknown ; model?: string ; parameters?: Record\<string, unknown> } | {}, options?: Options & { chatCompletion?: boolean ; task?: string ; taskHint?: InferenceTask }) => Promise\<unknown>

Type declaration

▸ (args, options?): Promise\<unknown>

Parameters

Name	Type
args	{ data: Blob | ArrayBuffer ; model?: string ; parameters?: Record\<string, unknown> } | { inputs: unknown ; model?: string ; parameters?: Record\<string, unknown> } | {}
options?	Options & { chatCompletion?: boolean ; task?: string ; taskHint?: InferenceTask }

Returns

Promise\<unknown>

Defined in

inference/src/tasks/custom/request.ts:7

---

sentenceSimilarity

• sentenceSimilarity: (args: { inputs: Record\<string, unknown> | Record\<string, unknown>[] ; model?: string }, options?: Options) => Promise\<SentenceSimilarityOutput>

Type declaration

▸ (args, options?): Promise\<SentenceSimilarityOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	Record\<string, unknown> | Record\<string, unknown>[]	The inputs vary based on the model. For example when using sentence-transformers/paraphrase-xlm-r-multilingual-v1 the inputs will have a source_sentence string and a sentences array of strings
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<SentenceSimilarityOutput>

Defined in

inference/src/tasks/nlp/sentenceSimilarity.ts:24

---

streamingRequest

• streamingRequest: (args: { data: Blob | ArrayBuffer ; model?: string ; parameters?: Record\<string, unknown> } | { inputs: unknown ; model?: string ; parameters?: Record\<string, unknown> } | {}, options?: Options & { chatCompletion?: boolean ; task?: string ; taskHint?: InferenceTask }) => AsyncGenerator\<unknown, any, unknown>

Type declaration

▸ (args, options?): AsyncGenerator\<unknown, any, unknown>

Parameters

Name	Type
args	{ data: Blob | ArrayBuffer ; model?: string ; parameters?: Record\<string, unknown> } | { inputs: unknown ; model?: string ; parameters?: Record\<string, unknown> } | {}
options?	Options & { chatCompletion?: boolean ; task?: string ; taskHint?: InferenceTask }

Returns

AsyncGenerator\<unknown, any, unknown>

Defined in

inference/src/tasks/custom/streamingRequest.ts:9

---

summarization

• summarization: (args: { inputs: string ; model?: string ; parameters?: { max_length?: number ; max_time?: number ; min_length?: number ; repetition_penalty?: number ; temperature?: number ; top_k?: number ; top_p?: number } }, options?: Options) => Promise\<SummarizationOutput>

Type declaration

▸ (args, options?): Promise\<SummarizationOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	string	A string to be summarized
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
args.parameters?	Object	-
args.parameters.max_length?	number	(Default: None). Integer to define the maximum length in tokens of the output summary.
args.parameters.max_time?	number	(Default: None). Float (0-120.0). The amount of time in seconds that the query should take maximum. Network can cause some overhead so it will be a soft limit.
args.parameters.min_length?	number	(Default: None). Integer to define the minimum length in tokens of the output summary.
args.parameters.repetition_penalty?	number	(Default: None). Float (0.0-100.0). The more a token is used within generation the more it is penalized to not be picked in successive generation passes.
args.parameters.temperature?	number	(Default: 1.0). Float (0.0-100.0). The temperature of the sampling operation. 1 means regular sampling, 0 means always take the highest score, 100.0 is getting closer to uniform probability.
args.parameters.top_k?	number	(Default: None). Integer to define the top tokens considered within the sample operation to create new text.
args.parameters.top_p?	number	(Default: None). Float to define the tokens that are within the sample operation of text generation. Add tokens in the sample for more probable to least probable until the sum of the probabilities is greater than top_p.
options?	Options	-

Returns

Promise\<SummarizationOutput>

Defined in

inference/src/tasks/nlp/summarization.ts:52

---

tableQuestionAnswering

• tableQuestionAnswering: (args: { inputs: { query: string ; table: Record\<string, string[]> } ; model?: string }, options?: Options) => Promise\<TableQuestionAnsweringOutput>

Type declaration

▸ (args, options?): Promise\<TableQuestionAnsweringOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	Object	-
args.inputs.query	string	The query in plain text that you want to ask the table
args.inputs.table	Record\<string, string[]>	A table of data represented as a dict of list where entries are headers and the lists are all the values, all lists must have the same size.
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<TableQuestionAnsweringOutput>

Defined in

inference/src/tasks/nlp/tableQuestionAnswering.ts:40

---

tabularClassification

• tabularClassification: (args: { inputs: { data: Record\<string, string[]> } ; model?: string }, options?: Options) => Promise\<TabularClassificationOutput>

Type declaration

▸ (args, options?): Promise\<TabularClassificationOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	Object	-
args.inputs.data	Record\<string, string[]>	A table of data represented as a dict of list where entries are headers and the lists are all the values, all lists must have the same size.
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<TabularClassificationOutput>

Defined in

inference/src/tasks/tabular/tabularClassification.ts:24

---

tabularRegression

• tabularRegression: (args: { inputs: { data: Record\<string, string[]> } ; model?: string }, options?: Options) => Promise\<TabularRegressionOutput>

Type declaration

▸ (args, options?): Promise\<TabularRegressionOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	Object	-
args.inputs.data	Record\<string, string[]>	A table of data represented as a dict of list where entries are headers and the lists are all the values, all lists must have the same size.
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<TabularRegressionOutput>

Defined in

inference/src/tasks/tabular/tabularRegression.ts:24

---

textClassification

• textClassification: (args: { inputs: string ; model?: string }, options?: Options) => Promise\<TextClassificationOutput>

Type declaration

▸ (args, options?): Promise\<TextClassificationOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	string	A string to be classified
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<TextClassificationOutput>

Defined in

inference/src/tasks/nlp/textClassification.ts:26

---

textGeneration

• textGeneration: (args: {}, options?: Options) => Promise\<TextGenerationOutput>

Type declaration

▸ (args, options?): Promise\<TextGenerationOutput>

Parameters

Name	Type
args	Object
options?	Options

Returns

Promise\<TextGenerationOutput>

Defined in

inference/src/tasks/nlp/textGeneration.ts:12

---

textGenerationStream

• textGenerationStream: (args: {}, options?: Options) => AsyncGenerator\<TextGenerationStreamOutput, any, unknown>

Type declaration

▸ (args, options?): AsyncGenerator\<TextGenerationStreamOutput, any, unknown>

Parameters

Name	Type
args	Object
options?	Options

Returns

AsyncGenerator\<TextGenerationStreamOutput, any, unknown>

Defined in

inference/src/tasks/nlp/textGenerationStream.ts:88

---

textToImage

• textToImage: (args: { inputs: string ; model?: string ; parameters?: { guidance_scale?: number ; height?: number ; negative_prompt?: string ; num_inference_steps?: number ; width?: number } }, options?: Options) => Promise\<Blob>

Type declaration

▸ (args, options?): Promise\<Blob>

Parameters

Name	Type	Description
args	Object	-
args.inputs	string	The text to generate an image from
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
args.parameters?	Object	-
args.parameters.guidance_scale?	number	Guidance scale: Higher guidance scale encourages to generate images that are closely linked to the text prompt, usually at the expense of lower image quality.
args.parameters.height?	number	The height in pixels of the generated image
args.parameters.negative_prompt?	string	An optional negative prompt for the image generation
args.parameters.num_inference_steps?	number	The number of denoising steps. More denoising steps usually lead to a higher quality image at the expense of slower inference.
args.parameters.width?	number	The width in pixels of the generated image
options?	Options	-

Returns

Promise\<Blob>

Defined in

inference/src/tasks/cv/textToImage.ts:41

---

textToSpeech

• textToSpeech: (args: { inputs: string ; model?: string }, options?: Options) => Promise\<Blob>

Type declaration

▸ (args, options?): Promise\<Blob>

Parameters

Name	Type	Description
args	Object	-
args.inputs	string	The text to generate an audio from
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<Blob>

Defined in

inference/src/tasks/audio/textToSpeech.ts:18

---

tokenClassification

• tokenClassification: (args: { inputs: string ; model?: string ; parameters?: { aggregation_strategy?: "none" | "simple" | "first" | "average" | "max" } }, options?: Options) => Promise\<TokenClassificationOutput>

Type declaration

▸ (args, options?): Promise\<TokenClassificationOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	string	A string to be classified
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
args.parameters?	Object	-
args.parameters.aggregation_strategy?	"none" | "simple" | "first" | "average" | "max"	(Default: simple). There are several aggregation strategies: none: Every token gets classified without further aggregation. simple: Entities are grouped according to the default schema (B-, I- tags get merged when the tag is similar). first: Same as the simple strategy except words cannot end up with different tags. Words will use the tag of the first token when there is ambiguity. average: Same as the simple strategy except words cannot end up with different tags. Scores are averaged across tokens and then the maximum label is applied. max: Same as the simple strategy except words cannot end up with different tags. Word entity will be the token with the maximum score.
options?	Options	-

Returns

Promise\<TokenClassificationOutput>

Defined in

inference/src/tasks/nlp/tokenClassification.ts:57

---

translation

• translation: (args: { inputs: string | string[] ; model?: string }, options?: Options) => Promise\<TranslationOutput>

Type declaration

▸ (args, options?): Promise\<TranslationOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	string | string[]	A string to be translated
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<TranslationOutput>

Defined in

inference/src/tasks/nlp/translation.ts:24

---

visualQuestionAnswering

• visualQuestionAnswering: (args: { inputs: { image: Blob | ArrayBuffer ; question: string } ; model?: string }, options?: Options) => Promise\<VisualQuestionAnsweringOutput>

Type declaration

▸ (args, options?): Promise\<VisualQuestionAnsweringOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	Object	-
args.inputs.image	Blob | ArrayBuffer	Raw image You can use native File in browsers, or new Blob([buffer]) in node, or for a base64 image new Blob([btoa(base64String)]), or even await (await fetch('...)).blob()
args.inputs.question	string	-
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
options?	Options	-

Returns

Promise\<VisualQuestionAnsweringOutput>

Defined in

inference/src/tasks/multimodal/visualQuestionAnswering.ts:32

---

zeroShotClassification

• zeroShotClassification: (args: { inputs: string | string[] ; model?: string ; parameters: { candidate_labels: string[] ; multi_label?: boolean } }, options?: Options) => Promise\<ZeroShotClassificationOutput>

Type declaration

▸ (args, options?): Promise\<ZeroShotClassificationOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	string | string[]	a string or list of strings
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
args.parameters	Object	-
args.parameters.candidate_labels	string[]	a list of strings that are potential classes for inputs. (max 10 candidate_labels, for more, simply run multiple requests, results are going to be misleading if using too many candidate_labels anyway. If you want to keep the exact same, you can simply run multi_label=True and do the scaling on your end.
args.parameters.multi_label?	boolean	(Default: false) Boolean that is set to True if classes can overlap
options?	Options	-

Returns

Promise\<ZeroShotClassificationOutput>

Defined in

inference/src/tasks/nlp/zeroShotClassification.ts:34

---

zeroShotImageClassification

• zeroShotImageClassification: (args: { inputs: { image: Blob | ArrayBuffer } ; model?: string ; parameters: { candidate_labels: string[] } }, options?: Options) => Promise\<ZeroShotImageClassificationOutput>

Type declaration

▸ (args, options?): Promise\<ZeroShotImageClassificationOutput>

Parameters

Name	Type	Description
args	Object	-
args.inputs	Object	-
args.inputs.image	Blob | ArrayBuffer	Binary image data
args.model?	string	The model to use. If not specified, will call huggingface.co/api/tasks to get the default model for the task. /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. Use the endpointUrl parameter instead.
args.parameters	Object	-
args.parameters.candidate_labels	string[]	A list of strings that are potential classes for inputs. (max 10)
options?	Options	-

Returns

Promise\<ZeroShotImageClassificationOutput>

Defined in

inference/src/tasks/cv/zeroShotImageClassification.ts:33

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