#
@huggingface/inference

##
Namespaces

- snippets

##
Classes

- HfInference
- InferenceClient
- InferenceClientEndpoint
- InferenceClientError
- InferenceClientHubApiError
- InferenceClientInputError
- InferenceClientProviderApiError
- InferenceClientProviderOutputError

##
Interfaces

- AudioToAudioOutput
- AudioToAudioOutputElem
- BaseArgs
- BodyParams
- HeaderParams
- InferenceProviderMappingEntry
- Logger
- Options
- TextGenerationInput
- TextGenerationOutput
- TextGenerationStreamBestOfSequence
- TextGenerationStreamDetails
- TextGenerationStreamOutput
- TextGenerationStreamPrefillToken
- TextGenerationStreamToken
- UrlParams

##
Type Aliases

###
AudioClassificationArgs

Ƭ AudioClassificationArgs: `BaseArgs` & `AudioClassificationInput` | `LegacyAudioInput`

####
Defined in

inference/src/tasks/audio/audioClassification.ts:9

###
AudioToAudioArgs

Ƭ AudioToAudioArgs: `BaseArgs` & { `inputs`: `Blob` } | `LegacyAudioInput`

####
Defined in

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

###
AuthMethod

Ƭ AuthMethod: `"none"` | `"hf-token"` | `"credentials-include"` | `"provider-key"`

####
Defined in

inference/src/types.ts:136

###
AutomaticSpeechRecognitionArgs

Ƭ AutomaticSpeechRecognitionArgs: `BaseArgs` & `AutomaticSpeechRecognitionInput` | `LegacyAudioInput`

####
Defined in

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

###
DocumentQuestionAnsweringArgs

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

####
Defined in

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

###
FeatureExtractionArgs

Ƭ FeatureExtractionArgs: `BaseArgs` & `FeatureExtractionInput` & `FeatureExtractionOAICompatInput`

####
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

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

###
FillMaskArgs

Ƭ FillMaskArgs: `BaseArgs` & `FillMaskInput`

####
Defined in

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

###
ImageClassificationArgs

Ƭ ImageClassificationArgs: `BaseArgs` & `ImageClassificationInput` | `LegacyImageInput`

####
Defined in

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

###
ImageSegmentationArgs

Ƭ ImageSegmentationArgs: `BaseArgs` & `ImageSegmentationInput`

####
Defined in

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

###
ImageToImageArgs

Ƭ ImageToImageArgs: `BaseArgs` & `ImageToImageInput`

####
Defined in

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

###
ImageToTextArgs

Ƭ ImageToTextArgs: `BaseArgs` & `ImageToTextInput` | `LegacyImageInput`

####
Defined in

inference/src/tasks/cv/imageToText.ts:9

###
ImageToVideoArgs

Ƭ ImageToVideoArgs: `BaseArgs` & `ImageToVideoInput`

####
Defined in

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

###
InferenceProvider

Ƭ InferenceProvider: typeof `INFERENCE_PROVIDERS`[`number`]

####
Defined in

inference/src/types.ts:74

###
InferenceProviderOrPolicy

Ƭ InferenceProviderOrPolicy: typeof `PROVIDERS_OR_POLICIES`[`number`]

####
Defined in

inference/src/types.ts:76

###
InferenceTask

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

####
Defined in

inference/src/types.ts:45

###
ModelId

Ƭ ModelId: `string`

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

####
Defined in

inference/src/types.ts:6

###
ObjectDetectionArgs

Ƭ ObjectDetectionArgs: `BaseArgs` & `ObjectDetectionInput` | `LegacyImageInput`

####
Defined in

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

###
QuestionAnsweringArgs

Ƭ QuestionAnsweringArgs: `BaseArgs` & `QuestionAnsweringInput`

####
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`> }

####
Defined in

inference/src/types.ts:124

###
SentenceSimilarityArgs

Ƭ SentenceSimilarityArgs: `BaseArgs` & `SentenceSimilarityInput`

####
Defined in

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

###
SummarizationArgs

Ƭ SummarizationArgs: `BaseArgs` & `SummarizationInput`

####
Defined in

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

###
TableQuestionAnsweringArgs

Ƭ TableQuestionAnsweringArgs: `BaseArgs` & `TableQuestionAnsweringInput`

####
Defined in

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

###
TabularClassificationArgs

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

####
Defined in

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

###
TabularClassificationOutput

Ƭ TabularClassificationOutput: `number`[]

A list of predicted labels for each row

####
Defined in

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

###
TabularRegressionArgs

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

####
Defined in

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

###
TabularRegressionOutput

Ƭ TabularRegressionOutput: `number`[]

a list of predicted values for each row

####
Defined in

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

###
TextClassificationArgs

Ƭ TextClassificationArgs: `BaseArgs` & `TextClassificationInput`

####
Defined in

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

###
TextGenerationStreamFinishReason

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

####
Defined in

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

###
TextToImageArgs

Ƭ TextToImageArgs: `BaseArgs` & `TextToImageInput`

####
Defined in

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

###
TextToVideoArgs

Ƭ TextToVideoArgs: `BaseArgs` & `TextToVideoInput`

####
Defined in

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

###
TextToVideoOutput

Ƭ TextToVideoOutput: `Blob`

####
Defined in

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

###
TokenClassificationArgs

Ƭ TokenClassificationArgs: `BaseArgs` & `TokenClassificationInput`

####
Defined in

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

###
TranslationArgs

Ƭ TranslationArgs: `BaseArgs` & `TranslationInput`

####
Defined in

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

###
VisualQuestionAnsweringArgs

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

####
Defined in

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

###
ZeroShotClassificationArgs

Ƭ ZeroShotClassificationArgs: `BaseArgs` & `ZeroShotClassificationInput`

####
Defined in

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

###
ZeroShotImageClassificationArgs

Ƭ ZeroShotImageClassificationArgs: `BaseArgs` & `ZeroShotImageClassificationInput` | `LegacyZeroShotImageClassificationInput`

####
Defined in

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

##
Variables

###
INFERENCE _ PROVIDERS

• `Const` INFERENCE_PROVIDERS: readonly [`"baseten"`, `"black-forest-labs"`, `"cerebras"`, `"clarifai"`, `"cohere"`, `"fal-ai"`, `"featherless-ai"`, `"fireworks-ai"`, `"groq"`, `"hf-inference"`, `"hyperbolic"`, `"nebius"`, `"novita"`, `"nscale"`, `"openai"`, `"ovhcloud"`, `"publicai"`, `"replicate"`, `"sambanova"`, `"scaleway"`, `"together"`, `"zai-org"`]

####
Defined in

inference/src/types.ts:47

###
PROVIDERS

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

####
Defined in

inference/src/lib/getProviderHelper.ts:59

###
PROVIDERS _ OR _ POLICIES

• `Const` PROVIDERS_OR_POLICIES: readonly [`"baseten"`, `"black-forest-labs"`, `"cerebras"`, `"clarifai"`, `"cohere"`, `"fal-ai"`, `"featherless-ai"`, `"fireworks-ai"`, `"groq"`, `"hf-inference"`, `"hyperbolic"`, `"nebius"`, `"novita"`, `"nscale"`, `"openai"`, `"ovhcloud"`, `"publicai"`, `"replicate"`, `"sambanova"`, `"scaleway"`, `"together"`, `"zai-org"`, `"auto"`]

####
Defined in

inference/src/types.ts:72

##
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

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

####
Returns

`Promise`\<`AudioClassificationOutput`>

####
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

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

####
Returns

`Promise`\<`AudioToAudioOutput`[]>

####
Defined in

inference/src/tasks/audio/audioToAudio.ts:39

###
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

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

####
Returns

`Promise`\<`AutomaticSpeechRecognitionOutput`>

####
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

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

####
Returns

`Promise`\<`ChatCompletionOutput`>

####
Defined in

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

###
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

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

####
Returns

`AsyncGenerator`\<`ChatCompletionStreamOutput`>

####
Defined in

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

###
documentQuestionAnswering

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

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

####
Parameters

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

####
Returns

`Promise`\<`DocumentQuestionAnsweringOutput`[`number`]>

####
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

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

####
Returns

`Promise`\<`FeatureExtractionOutput`>

####
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

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

####
Returns

`Promise`\<`FillMaskOutput`>

####
Defined in

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

###
getProviderHelper

▸ getProviderHelper(`provider`, `task`): `TextToImageTaskHelper` & `TaskProviderHelper`

Get provider helper instance by name and task

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"text-to-image"`

####
Returns

`TextToImageTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:184

▸ getProviderHelper(`provider`, `task`): `ConversationalTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"conversational"`

####
Returns

`ConversationalTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:188

▸ getProviderHelper(`provider`, `task`): `TextGenerationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"text-generation"`

####
Returns

`TextGenerationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:192

▸ getProviderHelper(`provider`, `task`): `TextToSpeechTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"text-to-speech"`

####
Returns

`TextToSpeechTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:196

▸ getProviderHelper(`provider`, `task`): `TextToAudioTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"text-to-audio"`

####
Returns

`TextToAudioTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:200

▸ getProviderHelper(`provider`, `task`): `AutomaticSpeechRecognitionTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"automatic-speech-recognition"`

####
Returns

`AutomaticSpeechRecognitionTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:204

▸ getProviderHelper(`provider`, `task`): `TextToVideoTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"text-to-video"`

####
Returns

`TextToVideoTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:208

▸ getProviderHelper(`provider`, `task`): `TextClassificationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"text-classification"`

####
Returns

`TextClassificationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:212

▸ getProviderHelper(`provider`, `task`): `QuestionAnsweringTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"question-answering"`

####
Returns

`QuestionAnsweringTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:216

▸ getProviderHelper(`provider`, `task`): `AudioClassificationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"audio-classification"`

####
Returns

`AudioClassificationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:220

▸ getProviderHelper(`provider`, `task`): `AudioToAudioTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"audio-to-audio"`

####
Returns

`AudioToAudioTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:224

▸ getProviderHelper(`provider`, `task`): `FillMaskTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"fill-mask"`

####
Returns

`FillMaskTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:228

▸ getProviderHelper(`provider`, `task`): `FeatureExtractionTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"feature-extraction"`

####
Returns

`FeatureExtractionTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:232

▸ getProviderHelper(`provider`, `task`): `ImageClassificationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"image-classification"`

####
Returns

`ImageClassificationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:236

▸ getProviderHelper(`provider`, `task`): `ImageSegmentationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"image-segmentation"`

####
Returns

`ImageSegmentationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:240

▸ getProviderHelper(`provider`, `task`): `DocumentQuestionAnsweringTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"document-question-answering"`

####
Returns

`DocumentQuestionAnsweringTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:244

▸ getProviderHelper(`provider`, `task`): `ImageToTextTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"image-to-text"`

####
Returns

`ImageToTextTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:248

▸ getProviderHelper(`provider`, `task`): `ObjectDetectionTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"object-detection"`

####
Returns

`ObjectDetectionTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:252

▸ getProviderHelper(`provider`, `task`): `ZeroShotImageClassificationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"zero-shot-image-classification"`

####
Returns

`ZeroShotImageClassificationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:256

▸ getProviderHelper(`provider`, `task`): `ZeroShotClassificationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"zero-shot-classification"`

####
Returns

`ZeroShotClassificationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:260

▸ getProviderHelper(`provider`, `task`): `ImageToImageTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"image-to-image"`

####
Returns

`ImageToImageTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:264

▸ getProviderHelper(`provider`, `task`): `ImageToVideoTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"image-to-video"`

####
Returns

`ImageToVideoTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:268

▸ getProviderHelper(`provider`, `task`): `SentenceSimilarityTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"sentence-similarity"`

####
Returns

`SentenceSimilarityTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:272

▸ getProviderHelper(`provider`, `task`): `TableQuestionAnsweringTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"table-question-answering"`

####
Returns

`TableQuestionAnsweringTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:276

▸ getProviderHelper(`provider`, `task`): `TabularClassificationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"tabular-classification"`

####
Returns

`TabularClassificationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:280

▸ getProviderHelper(`provider`, `task`): `TabularRegressionTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"tabular-regression"`

####
Returns

`TabularRegressionTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:284

▸ getProviderHelper(`provider`, `task`): `TokenClassificationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"token-classification"`

####
Returns

`TokenClassificationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:288

▸ getProviderHelper(`provider`, `task`): `TranslationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"translation"`

####
Returns

`TranslationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:292

▸ getProviderHelper(`provider`, `task`): `SummarizationTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"summarization"`

####
Returns

`SummarizationTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:296

▸ getProviderHelper(`provider`, `task`): `VisualQuestionAnsweringTaskHelper` & `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `"visual-question-answering"`

####
Returns

`VisualQuestionAnsweringTaskHelper` & `TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:300

▸ getProviderHelper(`provider`, `task`): `TaskProviderHelper`

####
Parameters

Name | Type
--- | ---
`provider` | `"baseten"` | `"black-forest-labs"` | `"cerebras"` | `"clarifai"` | `"cohere"` | `"fal-ai"` | `"featherless-ai"` | `"fireworks-ai"` | `"groq"` | `"hf-inference"` | `"hyperbolic"` | `"nebius"` | `"novita"` | `"nscale"` | `"openai"` | `"ovhcloud"` | `"publicai"` | `"replicate"` | `"sambanova"` | `"scaleway"` | `"together"` | `"zai-org"` | `"auto"`
`task` | `undefined` | `InferenceTask`

####
Returns

`TaskProviderHelper`

####
Defined in

inference/src/lib/getProviderHelper.ts:304

###
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

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

####
Returns

`Promise`\<`ImageClassificationOutput`>

####
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

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

####
Returns

`Promise`\<`ImageSegmentationOutput`>

####
Defined in

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

###
imageToImage

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

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

####
Parameters

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

####
Returns

`Promise`\<`Blob`>

####
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

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

####
Returns

`Promise`\<`ImageToTextOutput`>

####
Defined in

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

###
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

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

####
Returns

`Promise`\<`Blob`>

####
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

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

####
Returns

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

####
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

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

####
Returns

`Object`

Name | Type
--- | ---
`info` | `RequestInit`
`url` | `string`

####
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

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

####
Returns

`Promise`\<`ObjectDetectionOutput`>

####
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

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

####
Returns

`Promise`\<`QuestionAnsweringOutput`[`number`]>

####
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

Name
`T`

####
Parameters

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

####
Returns

`Promise`\<`T`>

`Deprecated`

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

####
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

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

####
Returns

`Promise`\<`SentenceSimilarityOutput`>

####
Defined in

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

###
setLogger

▸ setLogger(`logger`): `void`

####
Parameters

Name | Type
--- | ---
`logger` | `Logger`

####
Returns

`void`

####
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

Name
`T`

####
Parameters

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

####
Returns

`AsyncGenerator`\<`T`>

`Deprecated`

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

####
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

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

####
Returns

`Promise`\<`SummarizationOutput`>

####
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

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

####
Returns

`Promise`\<`TableQuestionAnsweringOutput`[`number`]>

####
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

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

####
Returns

`Promise`\<`TabularClassificationOutput`>

####
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

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

####
Returns

`Promise`\<`TabularRegressionOutput`>

####
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

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

####
Returns

`Promise`\<`TextClassificationOutput`>

####
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

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

####
Returns

`Promise`\<`TextGenerationOutput`>

####
Defined in

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

###
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

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

####
Returns

`AsyncGenerator`\<`TextGenerationStreamOutput`>

####
Defined in

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

###
textToImage

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

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

####
Parameters

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

####
Returns

`Promise`\<`string`>

####
Defined in

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

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

####
Parameters

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

####
Returns

`Promise`\<`Blob`>

####
Defined in

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

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

####
Parameters

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

####
Returns

`Promise`\<`Record`\<`string`, `unknown`>>

####
Defined in

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

###
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

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

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Returns

`Promise`\<`Blob`>

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Defined in

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

###
textToVideo

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

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Parameters

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

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Returns

`Promise`\<`TextToVideoOutput`>

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Defined in

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

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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

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Parameters

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

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Returns

`Promise`\<`TokenClassificationOutput`>

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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.

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Parameters

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

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Returns

`Promise`\<`TranslationOutput`>

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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.

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Parameters

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

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Returns

`Promise`\<`VisualQuestionAnsweringOutput`[`number`]>

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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.

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Parameters

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

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Returns

`Promise`\<`ZeroShotClassificationOutput`>

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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

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Parameters

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

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Returns

`Promise`\<`ZeroShotImageClassificationOutput`>

####
Defined in

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

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