Buckets:

hf-doc-build
/

doc-dev

Ƭ DocumentQuestionAnsweringArgs: BaseArgs & DocumentQuestionAnsweringInput & { inputs: DocumentQuestionAnsweringInputData & { image: Blob } }

Defined in[[documentquestionansweringargs.defined-in]]

inference/src/tasks/multimodal/documentQuestionAnswering.ts:13

FeatureExtractionArgs

Ƭ FeatureExtractionArgs: BaseArgs & FeatureExtractionInput & FeatureExtractionOAICompatInput

Defined in[[featureextractionargs.defined-in]]

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

FeatureExtractionOutput

Ƭ FeatureExtractionOutput: (number | number[] | number[][])[]

Returned values are a multidimensional array of floats (dimension depending on if you sent a string or a list of string, and if the automatic reduction, usually mean_pooling for instance was applied for you or not. This should be explained on the model's README).

Defined in[[featureextractionoutput.defined-in]]

inference/src/tasks/nlp/featureExtraction.ts:17

FillMaskArgs

Ƭ FillMaskArgs: BaseArgs & FillMaskInput

Defined in[[fillmaskargs.defined-in]]

inference/src/tasks/nlp/fillMask.ts:7

ImageClassificationArgs

Ƭ ImageClassificationArgs: BaseArgs & ImageClassificationInput | LegacyImageInput

Defined in[[imageclassificationargs.defined-in]]

inference/src/tasks/cv/imageClassification.ts:8

ImageSegmentationArgs

Ƭ ImageSegmentationArgs: BaseArgs & ImageSegmentationInput

Defined in[[imagesegmentationargs.defined-in]]

inference/src/tasks/cv/imageSegmentation.ts:8

ImageTextToImageArgs

Ƭ ImageTextToImageArgs: BaseArgs & ImageTextToImageInput

Defined in[[imagetexttoimageargs.defined-in]]

inference/src/tasks/cv/imageTextToImage.ts:7

ImageTextToVideoArgs

Ƭ ImageTextToVideoArgs: BaseArgs & ImageTextToVideoInput

Defined in[[imagetexttovideoargs.defined-in]]

inference/src/tasks/cv/imageTextToVideo.ts:7

ImageToImageArgs

Ƭ ImageToImageArgs: BaseArgs & ImageToImageInput

Defined in[[imagetoimageargs.defined-in]]

inference/src/tasks/cv/imageToImage.ts:8

ImageToTextArgs

Ƭ ImageToTextArgs: BaseArgs & ImageToTextInput | LegacyImageInput

Defined in[[imagetotextargs.defined-in]]

inference/src/tasks/cv/imageToText.ts:8

ImageToVideoArgs

Ƭ ImageToVideoArgs: BaseArgs & ImageToVideoInput

Defined in[[imagetovideoargs.defined-in]]

inference/src/tasks/cv/imageToVideo.ts:8

InferenceProvider

Ƭ InferenceProvider: typeof INFERENCE_PROVIDERS[number]

Defined in[[inferenceprovider.defined-in]]

inference/src/types.ts:71

InferenceProviderOrPolicy

Ƭ InferenceProviderOrPolicy: typeof PROVIDERS_OR_POLICIES[number]

Defined in[[inferenceproviderorpolicy.defined-in]]

inference/src/types.ts:73

InferenceTask

Ƭ InferenceTask: Exclude<PipelineType, "other"> | "conversational"

Defined in[[inferencetask.defined-in]]

inference/src/types.ts:45

ModelId

Ƭ ModelId: string

HF model id, like "meta-llama/Llama-3.3-70B-Instruct"

Defined in[[modelid.defined-in]]

inference/src/types.ts:6

ObjectDetectionArgs

Ƭ ObjectDetectionArgs: BaseArgs & ObjectDetectionInput | LegacyImageInput

Defined in[[objectdetectionargs.defined-in]]

inference/src/tasks/cv/objectDetection.ts:8

OutputType

Ƭ OutputType: "url" | "dataUrl" | "blob" | "json"

Defined in[[outputtype.defined-in]]

inference/src/types.ts:175

QuestionAnsweringArgs

Ƭ QuestionAnsweringArgs: BaseArgs & QuestionAnsweringInput

Defined in[[questionansweringargs.defined-in]]

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

RequestArgs

Ƭ RequestArgs: BaseArgs & { data: Blob | ArrayBuffer } | { inputs: unknown } | { prompt: string } | { text: string } | { audio_url: string } | ChatCompletionInput & { parameters?: Record<string, unknown> ; urlTransform?: (url: string) => string }

Defined in[[requestargs.defined-in]]

inference/src/types.ts:148

SentenceSimilarityArgs

Ƭ SentenceSimilarityArgs: BaseArgs & SentenceSimilarityInput

Defined in[[sentencesimilarityargs.defined-in]]

inference/src/tasks/nlp/sentenceSimilarity.ts:7

SummarizationArgs

Ƭ SummarizationArgs: BaseArgs & SummarizationInput

Defined in[[summarizationargs.defined-in]]

inference/src/tasks/nlp/summarization.ts:7

TableQuestionAnsweringArgs

Ƭ TableQuestionAnsweringArgs: BaseArgs & TableQuestionAnsweringInput

Defined in[[tablequestionansweringargs.defined-in]]

inference/src/tasks/nlp/tableQuestionAnswering.ts:7

TabularClassificationArgs

Ƭ TabularClassificationArgs: BaseArgs & { inputs: { data: Record<string, string[]> } }

Defined in[[tabularclassificationargs.defined-in]]

inference/src/tasks/tabular/tabularClassification.ts:6

TabularClassificationOutput

Ƭ TabularClassificationOutput: number[]

A list of predicted labels for each row

Defined in[[tabularclassificationoutput.defined-in]]

inference/src/tasks/tabular/tabularClassification.ts:18

TabularRegressionArgs

Ƭ TabularRegressionArgs: BaseArgs & { inputs: { data: Record<string, string[]> } }

Defined in[[tabularregressionargs.defined-in]]

inference/src/tasks/tabular/tabularRegression.ts:6

TabularRegressionOutput

Ƭ TabularRegressionOutput: number[]

a list of predicted values for each row

Defined in[[tabularregressionoutput.defined-in]]

inference/src/tasks/tabular/tabularRegression.ts:18

TextClassificationArgs

Ƭ TextClassificationArgs: BaseArgs & TextClassificationInput

Defined in[[textclassificationargs.defined-in]]

inference/src/tasks/nlp/textClassification.ts:7

TextGenerationStreamFinishReason

Ƭ TextGenerationStreamFinishReason: "length" | "eos_token" | "stop_sequence"

Defined in[[textgenerationstreamfinishreason.defined-in]]

inference/src/tasks/nlp/textGenerationStream.ts:48

TextToAudioArgs

Ƭ TextToAudioArgs: BaseArgs & TextToAudioInput

Defined in[[texttoaudioargs.defined-in]]

inference/src/tasks/audio/textToAudio.ts:8

TextToImageArgs

Ƭ TextToImageArgs: BaseArgs & TextToImageInput

Defined in[[texttoimageargs.defined-in]]

inference/src/tasks/cv/textToImage.ts:8

TextToVideoArgs

Ƭ TextToVideoArgs: BaseArgs & TextToVideoInput

Defined in[[texttovideoargs.defined-in]]

inference/src/tasks/cv/textToVideo.ts:11

TextToVideoOutput

Ƭ TextToVideoOutput: Blob

Defined in[[texttovideooutput.defined-in]]

inference/src/tasks/cv/textToVideo.ts:13

TokenClassificationArgs

Ƭ TokenClassificationArgs: BaseArgs & TokenClassificationInput

Defined in[[tokenclassificationargs.defined-in]]

inference/src/tasks/nlp/tokenClassification.ts:7

TranslationArgs

Ƭ TranslationArgs: BaseArgs & TranslationInput

Defined in[[translationargs.defined-in]]

inference/src/tasks/nlp/translation.ts:7

VisualQuestionAnsweringArgs

Ƭ VisualQuestionAnsweringArgs: BaseArgs & VisualQuestionAnsweringInput & { inputs: VisualQuestionAnsweringInputData & { image: Blob } }

Defined in[[visualquestionansweringargs.defined-in]]

inference/src/tasks/multimodal/visualQuestionAnswering.ts:13

ZeroShotClassificationArgs

Ƭ ZeroShotClassificationArgs: BaseArgs & ZeroShotClassificationInput

Defined in[[zeroshotclassificationargs.defined-in]]

inference/src/tasks/nlp/zeroShotClassification.ts:7

ZeroShotImageClassificationArgs

Ƭ ZeroShotImageClassificationArgs: BaseArgs & ZeroShotImageClassificationInput | LegacyZeroShotImageClassificationInput

Defined in[[zeroshotimageclassificationargs.defined-in]]

inference/src/tasks/cv/zeroShotImageClassification.ts:15

Variables

INFERENCE_PROVIDERS

• Const INFERENCE_PROVIDERS: readonly ["baseten", "cerebras", "cohere", "deepinfra", "fal-ai", "featherless-ai", "fireworks-ai", "groq", "hf-inference", "novita", "nscale", "openai", "ovhcloud", "publicai", "replicate", "scaleway", "together", "wavespeed", "zai-org"]

Defined in[[inferenceproviders.defined-in]]

inference/src/types.ts:47

PROVIDERS

• Const PROVIDERS: Record<InferenceProvider, Partial<Record<InferenceTask, TaskProviderHelper>>>

Defined in[[providers.defined-in]]

inference/src/lib/getProviderHelper.ts:58

PROVIDERS_HUB_ORGS

• Const PROVIDERS_HUB_ORGS: Record<InferenceProvider, string>

The org namespace on the HF Hub i.e. hf.co/…

Whenever possible, InferenceProvider should == org namespace

Defined in[[providershuborgs.defined-in]]

inference/src/types.ts:80

PROVIDERS_OR_POLICIES

• Const PROVIDERS_OR_POLICIES: readonly ["baseten", "cerebras", "cohere", "deepinfra", "fal-ai", "featherless-ai", "fireworks-ai", "groq", "hf-inference", "novita", "nscale", "openai", "ovhcloud", "publicai", "replicate", "scaleway", "together", "wavespeed", "zai-org", "auto"]

Defined in[[providersorpolicies.defined-in]]

inference/src/types.ts:69

Functions

audioClassification

▸ audioClassification(args, options?): Promise<AudioClassificationOutput>

This task reads some audio input and outputs the likelihood of classes. Recommended model: superb/hubert-large-superb-er

Parameters[[audioclassification.parameters]]

Name	Type
`args`	`AudioClassificationArgs`
`options?`	`Options`

Returns[[audioclassification.returns]]

Promise<AudioClassificationOutput>

Defined in[[audioclassification.defined-in]]

inference/src/tasks/audio/audioClassification.ts:15

audioToAudio

▸ audioToAudio(args, options?): Promise<AudioToAudioOutput[]>

This task reads some audio input and outputs one or multiple audio files. Example model: speechbrain/sepformer-wham does audio source separation.

Parameters[[audiotoaudio.parameters]]

Name	Type
`args`	`AudioToAudioArgs`
`options?`	`Options`

Returns[[audiotoaudio.returns]]

Promise<AudioToAudioOutput[]>

Defined in[[audiotoaudio.defined-in]]

inference/src/tasks/audio/audioToAudio.ts:41

automaticSpeechRecognition

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

This task reads some audio input and outputs the said words within the audio files. Recommended model (english language): facebook/wav2vec2-large-960h-lv60-self

Parameters[[automaticspeechrecognition.parameters]]

Name	Type
`args`	`AutomaticSpeechRecognitionArgs`
`options?`	`Options`

Returns[[automaticspeechrecognition.returns]]

Promise<AutomaticSpeechRecognitionOutput>

Defined in[[automaticspeechrecognition.defined-in]]

inference/src/tasks/audio/automaticSpeechRecognition.ts:13

chatCompletion

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

Use the chat completion endpoint to generate a response to a prompt, using OpenAI message completion API no stream

Parameters[[chatcompletion.parameters]]

Name	Type
`args`	`BaseArgs` & `ChatCompletionInput`
`options?`	`Options`

Returns[[chatcompletion.returns]]

Promise<ChatCompletionOutput>

Defined in[[chatcompletion.defined-in]]

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

chatCompletionStream

▸ chatCompletionStream(args, options?): AsyncGenerator<ChatCompletionStreamOutput>

Use to continue text from a prompt. Same as textGeneration but returns generator that can be read one token at a time

Parameters[[chatcompletionstream.parameters]]

Name	Type
`args`	`BaseArgs` & `ChatCompletionInput`
`options?`	`Options`

Returns[[chatcompletionstream.returns]]

AsyncGenerator<ChatCompletionStreamOutput>

Defined in[[chatcompletionstream.defined-in]]

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

documentQuestionAnswering

▸ documentQuestionAnswering(args, options?): Promise<DocumentQuestionAnsweringOutput[number]>

Answers a question on a document image. Recommended model: impira/layoutlm-document-qa.

Parameters[[documentquestionanswering.parameters]]

Name	Type
`args`	`DocumentQuestionAnsweringArgs`
`options?`	`Options`

Returns[[documentquestionanswering.returns]]

Promise<DocumentQuestionAnsweringOutput[number]>

Defined in[[documentquestionanswering.defined-in]]

inference/src/tasks/multimodal/documentQuestionAnswering.ts:19

featureExtraction

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

This task reads some text and outputs raw float values, that are usually consumed as part of a semantic database/semantic search.

Parameters[[featureextraction.parameters]]

Name	Type
`args`	`FeatureExtractionArgs`
`options?`	`Options`

Returns[[featureextraction.returns]]

Promise<FeatureExtractionOutput>

Defined in[[featureextraction.defined-in]]

inference/src/tasks/nlp/featureExtraction.ts:22

fillMask

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

Tries to fill in a hole with a missing word (token to be precise). That’s the base task for BERT models.

Parameters[[fillmask.parameters]]

Name	Type
`args`	`FillMaskArgs`
`options?`	`Options`

Returns[[fillmask.returns]]

Promise<FillMaskOutput>

Defined in[[fillmask.defined-in]]

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

getProviderHelper

▸ getProviderHelper(provider, task): TextToImageTaskHelper & TaskProviderHelper

Get provider helper instance by name and task

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"text-to-image"`

Returns[[getproviderhelper.returns]]

TextToImageTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:189

▸ getProviderHelper(provider, task): ConversationalTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"conversational"`

Returns[[getproviderhelper.returns]]

ConversationalTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:193

▸ getProviderHelper(provider, task): TextGenerationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"text-generation"`

Returns[[getproviderhelper.returns]]

TextGenerationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:197

▸ getProviderHelper(provider, task): TextToSpeechTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"text-to-speech"`

Returns[[getproviderhelper.returns]]

TextToSpeechTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:201

▸ getProviderHelper(provider, task): TextToAudioTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"text-to-audio"`

Returns[[getproviderhelper.returns]]

TextToAudioTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:205

▸ getProviderHelper(provider, task): AutomaticSpeechRecognitionTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"automatic-speech-recognition"`

Returns[[getproviderhelper.returns]]

AutomaticSpeechRecognitionTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:209

▸ getProviderHelper(provider, task): TextToVideoTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"text-to-video"`

Returns[[getproviderhelper.returns]]

TextToVideoTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:213

▸ getProviderHelper(provider, task): TextClassificationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"text-classification"`

Returns[[getproviderhelper.returns]]

TextClassificationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:217

▸ getProviderHelper(provider, task): QuestionAnsweringTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"question-answering"`

Returns[[getproviderhelper.returns]]

QuestionAnsweringTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:221

▸ getProviderHelper(provider, task): AudioClassificationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"audio-classification"`

Returns[[getproviderhelper.returns]]

AudioClassificationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:225

▸ getProviderHelper(provider, task): AudioToAudioTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"audio-to-audio"`

Returns[[getproviderhelper.returns]]

AudioToAudioTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:229

▸ getProviderHelper(provider, task): FillMaskTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"fill-mask"`

Returns[[getproviderhelper.returns]]

FillMaskTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:233

▸ getProviderHelper(provider, task): FeatureExtractionTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"feature-extraction"`

Returns[[getproviderhelper.returns]]

FeatureExtractionTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:237

▸ getProviderHelper(provider, task): ImageClassificationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"image-classification"`

Returns[[getproviderhelper.returns]]

ImageClassificationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:241

▸ getProviderHelper(provider, task): ImageSegmentationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"image-segmentation"`

Returns[[getproviderhelper.returns]]

ImageSegmentationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:245

▸ getProviderHelper(provider, task): DocumentQuestionAnsweringTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"document-question-answering"`

Returns[[getproviderhelper.returns]]

DocumentQuestionAnsweringTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:249

▸ getProviderHelper(provider, task): ImageToTextTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"image-to-text"`

Returns[[getproviderhelper.returns]]

ImageToTextTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:253

▸ getProviderHelper(provider, task): ObjectDetectionTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"object-detection"`

Returns[[getproviderhelper.returns]]

ObjectDetectionTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:257

▸ getProviderHelper(provider, task): ZeroShotImageClassificationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"zero-shot-image-classification"`

Returns[[getproviderhelper.returns]]

ZeroShotImageClassificationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:261

▸ getProviderHelper(provider, task): ZeroShotClassificationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"zero-shot-classification"`

Returns[[getproviderhelper.returns]]

ZeroShotClassificationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:265

▸ getProviderHelper(provider, task): ImageToImageTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"image-to-image"`

Returns[[getproviderhelper.returns]]

ImageToImageTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:269

▸ getProviderHelper(provider, task): ImageToVideoTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"image-to-video"`

Returns[[getproviderhelper.returns]]

ImageToVideoTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:273

▸ getProviderHelper(provider, task): ImageTextToImageTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"image-text-to-image"`

Returns[[getproviderhelper.returns]]

ImageTextToImageTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:277

▸ getProviderHelper(provider, task): ImageTextToVideoTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"image-text-to-video"`

Returns[[getproviderhelper.returns]]

ImageTextToVideoTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:281

▸ getProviderHelper(provider, task): SentenceSimilarityTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"sentence-similarity"`

Returns[[getproviderhelper.returns]]

SentenceSimilarityTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:285

▸ getProviderHelper(provider, task): TableQuestionAnsweringTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"table-question-answering"`

Returns[[getproviderhelper.returns]]

TableQuestionAnsweringTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:289

▸ getProviderHelper(provider, task): TabularClassificationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"tabular-classification"`

Returns[[getproviderhelper.returns]]

TabularClassificationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:293

▸ getProviderHelper(provider, task): TabularRegressionTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"tabular-regression"`

Returns[[getproviderhelper.returns]]

TabularRegressionTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:297

▸ getProviderHelper(provider, task): TokenClassificationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"token-classification"`

Returns[[getproviderhelper.returns]]

TokenClassificationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:301

▸ getProviderHelper(provider, task): TranslationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"translation"`

Returns[[getproviderhelper.returns]]

TranslationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:305

▸ getProviderHelper(provider, task): SummarizationTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"summarization"`

Returns[[getproviderhelper.returns]]

SummarizationTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:309

▸ getProviderHelper(provider, task): VisualQuestionAnsweringTaskHelper & TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`"visual-question-answering"`

Returns[[getproviderhelper.returns]]

VisualQuestionAnsweringTaskHelper & TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:313

▸ getProviderHelper(provider, task): TaskProviderHelper

Parameters[[getproviderhelper.parameters]]

Name	Type
`provider`	`"baseten"` \| `"cerebras"` \| `"cohere"` \| `"deepinfra"` \| `"fal-ai"` \| `"featherless-ai"` \| `"fireworks-ai"` \| `"groq"` \| `"hf-inference"` \| `"novita"` \| `"nscale"` \| `"openai"` \| `"ovhcloud"` \| `"publicai"` \| `"replicate"` \| `"scaleway"` \| `"together"` \| `"wavespeed"` \| `"zai-org"` \| `"auto"`
`task`	`undefined` \| `InferenceTask`

Returns[[getproviderhelper.returns]]

TaskProviderHelper

Defined in[[getproviderhelper.defined-in]]

inference/src/lib/getProviderHelper.ts:317

imageClassification

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

This task reads some image input and outputs the likelihood of classes. Recommended model: google/vit-base-patch16-224

Parameters[[imageclassification.parameters]]

Name	Type
`args`	`ImageClassificationArgs`
`options?`	`Options`

Returns[[imageclassification.returns]]

Promise<ImageClassificationOutput>

Defined in[[imageclassification.defined-in]]

inference/src/tasks/cv/imageClassification.ts:14

imageSegmentation

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

This task reads some image input and outputs the likelihood of classes & bounding boxes of detected objects. Recommended model: facebook/detr-resnet-50-panoptic

Parameters[[imagesegmentation.parameters]]

Name	Type
`args`	`ImageSegmentationArgs`
`options?`	`Options`

Returns[[imagesegmentation.returns]]

Promise<ImageSegmentationOutput>

Defined in[[imagesegmentation.defined-in]]

inference/src/tasks/cv/imageSegmentation.ts:14

imageTextToImage

▸ imageTextToImage(args, options?): Promise<Blob>

This task takes an image and text input and outputs a new generated image. Recommended model: black-forest-labs/FLUX.2-dev

Parameters[[imagetexttoimage.parameters]]

Name	Type
`args`	`ImageTextToImageArgs`
`options?`	`Options`

Returns[[imagetexttoimage.returns]]

Promise<Blob>

Defined in[[imagetexttoimage.defined-in]]

inference/src/tasks/cv/imageTextToImage.ts:13

imageTextToVideo

▸ imageTextToVideo(args, options?): Promise<Blob>

This task takes an image and text input and outputs a generated video. Recommended model: Lightricks/LTX-Video

Parameters[[imagetexttovideo.parameters]]

Name	Type
`args`	`ImageTextToVideoArgs`
`options?`	`Options`

Returns[[imagetexttovideo.returns]]

Promise<Blob>

Defined in[[imagetexttovideo.defined-in]]

inference/src/tasks/cv/imageTextToVideo.ts:13

imageToImage

▸ imageToImage(args, options?): Promise<Blob>

This task reads some text input and outputs an image. Recommended model: lllyasviel/sd-controlnet-depth

Parameters[[imagetoimage.parameters]]

Name	Type
`args`	`ImageToImageArgs`
`options?`	`Options`

Returns[[imagetoimage.returns]]

Promise<Blob>

Defined in[[imagetoimage.defined-in]]

inference/src/tasks/cv/imageToImage.ts:14

imageToText

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

This task reads some image input and outputs the text caption.

Parameters[[imagetotext.parameters]]

Name	Type
`args`	`ImageToTextArgs`
`options?`	`Options`

Returns[[imagetotext.returns]]

Promise<ImageToTextOutput>

Defined in[[imagetotext.defined-in]]

inference/src/tasks/cv/imageToText.ts:12

imageToVideo

▸ imageToVideo(args, options?): Promise<Blob>

This task reads some text input and outputs an image. Recommended model: Wan-AI/Wan2.1-I2V-14B-720P

Parameters[[imagetovideo.parameters]]

Name	Type
`args`	`ImageToVideoArgs`
`options?`	`Options`

Returns[[imagetovideo.returns]]

Promise<Blob>

Defined in[[imagetovideo.defined-in]]

inference/src/tasks/cv/imageToVideo.ts:14

makeRequestOptions

▸ makeRequestOptions(args, providerHelper, options?): Promise<{ info: RequestInit ; url: string }>

Helper that prepares request arguments. This async version handle the model ID resolution step.

Parameters[[makerequestoptions.parameters]]

Name	Type
`args`	`RequestArgs` & { `data?`: `Blob` \| `ArrayBuffer` ; `stream?`: `boolean` }
`providerHelper`	`TaskProviderHelper`
`options?`	`Options` & { `task?`: `InferenceTask` }

Returns[[makerequestoptions.returns]]

Promise<{ info: RequestInit ; url: string }>

Defined in[[makerequestoptions.defined-in]]

inference/src/lib/makeRequestOptions.ts:19

makeRequestOptionsFromResolvedModel

▸ makeRequestOptionsFromResolvedModel(resolvedModel, providerHelper, args, mapping, options?): Object

Helper that prepares request arguments. - for internal use only This sync version skips the model ID resolution step

Parameters[[makerequestoptionsfromresolvedmodel.parameters]]

Name	Type
`resolvedModel`	`string`
`providerHelper`	`TaskProviderHelper`
`args`	`RequestArgs` & { `data?`: `Blob` \| `ArrayBuffer` ; `stream?`: `boolean` }
`mapping`	`undefined` \| `InferenceProviderMappingEntry`
`options?`	`Options` & { `outputType?`: `OutputType` ; `task?`: `InferenceTask` }

Returns[[makerequestoptionsfromresolvedmodel.returns]]

Object

Name	Type
`info`	`RequestInit`
`url`	`string`

Defined in[[makerequestoptionsfromresolvedmodel.defined-in]]

inference/src/lib/makeRequestOptions.ts:105

objectDetection

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

This task reads some image input and outputs the likelihood of classes & bounding boxes of detected objects. Recommended model: facebook/detr-resnet-50

Parameters[[objectdetection.parameters]]

Name	Type
`args`	`ObjectDetectionArgs`
`options?`	`Options`

Returns[[objectdetection.returns]]

Promise<ObjectDetectionOutput>

Defined in[[objectdetection.defined-in]]

inference/src/tasks/cv/objectDetection.ts:14

questionAnswering

▸ questionAnswering(args, options?): Promise<QuestionAnsweringOutput[number]>

Want to have a nice know-it-all bot that can answer any question?. Recommended model: deepset/roberta-base-squad2

Parameters[[questionanswering.parameters]]

Name	Type
`args`	`QuestionAnsweringArgs`
`options?`	`Options`

Returns[[questionanswering.returns]]

Promise<QuestionAnsweringOutput[number]>

Defined in[[questionanswering.defined-in]]

inference/src/tasks/nlp/questionAnswering.ts:13

request

▸ request<T>(args, options?): Promise<T>

Primitive to make custom calls to the inference provider

Type parameters[[request.type-parameters]]

Name
`T`

Parameters[[request.parameters]]

Name	Type
`args`	`RequestArgs`
`options?`	`Options` & { `task?`: `InferenceTask` }

Returns[[request.returns]]

Promise<T>

Deprecated

Use specific task functions instead. This function will be removed in a future version.

Defined in[[request.defined-in]]

inference/src/tasks/custom/request.ts:11

sentenceSimilarity

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

Calculate the semantic similarity between one text and a list of other sentences by comparing their embeddings.

Parameters[[sentencesimilarity.parameters]]

Name	Type
`args`	`SentenceSimilarityArgs`
`options?`	`Options`

Returns[[sentencesimilarity.returns]]

Promise<SentenceSimilarityOutput>

Defined in[[sentencesimilarity.defined-in]]

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

setLogger

▸ setLogger(logger): void

Parameters[[setlogger.parameters]]

Name	Type
`logger`	`Logger`

Returns[[setlogger.returns]]

void

Defined in[[setlogger.defined-in]]

inference/src/lib/logger.ts:5

streamingRequest

▸ streamingRequest<T>(args, options?): AsyncGenerator<T>

Primitive to make custom inference calls that expect server-sent events, and returns the response through a generator

Type parameters[[streamingrequest.type-parameters]]

Name
`T`

Parameters[[streamingrequest.parameters]]

Name	Type
`args`	`RequestArgs`
`options?`	`Options` & { `task?`: `InferenceTask` }

Returns[[streamingrequest.returns]]

AsyncGenerator<T>

Deprecated

Use specific task functions instead. This function will be removed in a future version.

Defined in[[streamingrequest.defined-in]]

inference/src/tasks/custom/streamingRequest.ts:11

summarization

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

This task is well known to summarize longer text into shorter text. Be careful, some models have a maximum length of input. That means that the summary cannot handle full books for instance. Be careful when choosing your model.

Parameters[[summarization.parameters]]

Name	Type
`args`	`SummarizationArgs`
`options?`	`Options`

Returns[[summarization.returns]]

Promise<SummarizationOutput>

Defined in[[summarization.defined-in]]

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

tableQuestionAnswering

▸ tableQuestionAnswering(args, options?): Promise<TableQuestionAnsweringOutput[number]>

Don’t know SQL? Don’t want to dive into a large spreadsheet? Ask questions in plain english! Recommended model: google/tapas-base-finetuned-wtq.

Parameters[[tablequestionanswering.parameters]]

Name	Type
`args`	`TableQuestionAnsweringArgs`
`options?`	`Options`

Returns[[tablequestionanswering.returns]]

Promise<TableQuestionAnsweringOutput[number]>

Defined in[[tablequestionanswering.defined-in]]

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

tabularClassification

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

Predicts target label for a given set of features in tabular form. Typically, you will want to train a classification model on your training data and use it with your new data of the same format. Example model: vvmnnnkv/wine-quality

Parameters[[tabularclassification.parameters]]

Name	Type
`args`	`TabularClassificationArgs`
`options?`	`Options`

Returns[[tabularclassification.returns]]

Promise<TabularClassificationOutput>

Defined in[[tabularclassification.defined-in]]

inference/src/tasks/tabular/tabularClassification.ts:25

tabularRegression

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

Predicts target value for a given set of features in tabular form. Typically, you will want to train a regression model on your training data and use it with your new data of the same format. Example model: scikit-learn/Fish-Weight

Parameters[[tabularregression.parameters]]

Name	Type
`args`	`TabularRegressionArgs`
`options?`	`Options`

Returns[[tabularregression.returns]]

Promise<TabularRegressionOutput>

Defined in[[tabularregression.defined-in]]

inference/src/tasks/tabular/tabularRegression.ts:25

textClassification

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

Usually used for sentiment-analysis this will output the likelihood of classes of an input. Recommended model: distilbert-base-uncased-finetuned-sst-2-english

Parameters[[textclassification.parameters]]

Name	Type
`args`	`TextClassificationArgs`
`options?`	`Options`

Returns[[textclassification.returns]]

Promise<TextClassificationOutput>

Defined in[[textclassification.defined-in]]

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

textGeneration

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

Use to continue text from a prompt. This is a very generic task. Recommended model: gpt2 (it’s a simple model, but fun to play with).

Parameters[[textgeneration.parameters]]

Name	Type
`args`	`BaseArgs` & `TextGenerationInput`
`options?`	`Options`

Returns[[textgeneration.returns]]

Promise<TextGenerationOutput>

Defined in[[textgeneration.defined-in]]

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

textGenerationStream

▸ textGenerationStream(args, options?): AsyncGenerator<TextGenerationStreamOutput>

Use to continue text from a prompt. Same as textGeneration but returns generator that can be read one token at a time

Parameters[[textgenerationstream.parameters]]

Name	Type
`args`	`BaseArgs` & `TextGenerationInput`
`options?`	`Options`

Returns[[textgenerationstream.returns]]

AsyncGenerator<TextGenerationStreamOutput>

Defined in[[textgenerationstream.defined-in]]

inference/src/tasks/nlp/textGenerationStream.ts:90

textToAudio

▸ textToAudio(args, options?): Promise<Blob>

This task generates audio (e.g. music or sound effects) from an input text prompt. Example model: stabilityai/stable-audio-open-1.0

Parameters[[texttoaudio.parameters]]

Name	Type
`args`	`TextToAudioArgs`
`options?`	`Options`

Returns[[texttoaudio.returns]]

Promise<Blob>

Defined in[[texttoaudio.defined-in]]

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

textToImage

▸ textToImage(args, options?): Promise<string>

This task reads some text input and outputs an image. Recommended model: stabilityai/stable-diffusion-2

Parameters[[texttoimage.parameters]]

Name	Type
`args`	`TextToImageArgs`
`options?`	`TextToImageOptions` & { `outputType`: `"url"` }

Returns[[texttoimage.returns]]

Promise<string>

Defined in[[texttoimage.defined-in]]

inference/src/tasks/cv/textToImage.ts:18

▸ textToImage(args, options?): Promise<string>

Parameters[[texttoimage.parameters]]

Name	Type
`args`	`TextToImageArgs`
`options?`	`TextToImageOptions` & { `outputType`: `"dataUrl"` }

Returns[[texttoimage.returns]]

Promise<string>

Defined in[[texttoimage.defined-in]]

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

▸ textToImage(args, options?): Promise<Blob>

Parameters[[texttoimage.parameters]]

Name	Type
`args`	`TextToImageArgs`
`options?`	`TextToImageOptions` & { `outputType?`: `"blob"` }

Returns[[texttoimage.returns]]

Promise<Blob>

Defined in[[texttoimage.defined-in]]

inference/src/tasks/cv/textToImage.ts:26

▸ textToImage(args, options?): Promise<Record<string, unknown>>

Parameters[[texttoimage.parameters]]

Name	Type
`args`	`TextToImageArgs`
`options?`	`TextToImageOptions` & { `outputType?`: `"json"` }

Returns[[texttoimage.returns]]

Promise<Record<string, unknown>>

Defined in[[texttoimage.defined-in]]

inference/src/tasks/cv/textToImage.ts:30

textToSpeech

▸ textToSpeech(args, options?): Promise<Blob>

This task synthesize an audio of a voice pronouncing a given text. Recommended model: espnet/kan-bayashi_ljspeech_vits

Parameters[[texttospeech.parameters]]

Name	Type
`args`	`TextToSpeechArgs`
`options?`	`Options`

Returns[[texttospeech.returns]]

Promise<Blob>

Defined in[[texttospeech.defined-in]]

inference/src/tasks/audio/textToSpeech.ts:15

textToVideo

▸ textToVideo(args, options?): Promise<TextToVideoOutput>

Parameters[[texttovideo.parameters]]

Name	Type
`args`	`TextToVideoArgs`
`options?`	`Options`

Returns[[texttovideo.returns]]

Promise<TextToVideoOutput>

Defined in[[texttovideo.defined-in]]

inference/src/tasks/cv/textToVideo.ts:15

tokenClassification

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

Usually used for sentence parsing, either grammatical, or Named Entity Recognition (NER) to understand keywords contained within text. Recommended model: dbmdz/bert-large-cased-finetuned-conll03-english

Parameters[[tokenclassification.parameters]]

Name	Type
`args`	`TokenClassificationArgs`
`options?`	`Options`

Returns[[tokenclassification.returns]]

Promise<TokenClassificationOutput>

Defined in[[tokenclassification.defined-in]]

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

translation

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

This task is well known to translate text from one language to another. Recommended model: Helsinki-NLP/opus-mt-ru-en.

Parameters[[translation.parameters]]

Name	Type
`args`	`TranslationArgs`
`options?`	`Options`

Returns[[translation.returns]]

Promise<TranslationOutput>

Defined in[[translation.defined-in]]

inference/src/tasks/nlp/translation.ts:11

visualQuestionAnswering

▸ visualQuestionAnswering(args, options?): Promise<VisualQuestionAnsweringOutput[number]>

Answers a question on an image. Recommended model: dandelin/vilt-b32-finetuned-vqa.

Parameters[[visualquestionanswering.parameters]]

Name	Type
`args`	`VisualQuestionAnsweringArgs`
`options?`	`Options`

Returns[[visualquestionanswering.returns]]

Promise<VisualQuestionAnsweringOutput[number]>

Defined in[[visualquestionanswering.defined-in]]

inference/src/tasks/multimodal/visualQuestionAnswering.ts:19

zeroShotClassification

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

This task is super useful to try out classification with zero code, you simply pass a sentence/paragraph and the possible labels for that sentence, and you get a result. Recommended model: facebook/bart-large-mnli.

Parameters[[zeroshotclassification.parameters]]

Name	Type
`args`	`ZeroShotClassificationArgs`
`options?`	`Options`

Returns[[zeroshotclassification.returns]]

Promise<ZeroShotClassificationOutput>

Defined in[[zeroshotclassification.defined-in]]

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

zeroShotImageClassification

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

Classify an image to specified classes. Recommended model: openai/clip-vit-large-patch14-336

Parameters[[zeroshotimageclassification.parameters]]

Name	Type
`args`	`ZeroShotImageClassificationArgs`
`options?`	`Options`

Returns[[zeroshotimageclassification.returns]]

Promise<ZeroShotImageClassificationOutput>

Defined in[[zeroshotimageclassification.defined-in]]

inference/src/tasks/cv/zeroShotImageClassification.ts:44

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