api-inference documentation

Translation

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Translation

Translation is the task of converting text from one language to another.

For more details about the translation task, check out its dedicated page! You will find examples and related materials.

Recommended models

  • google-t5/t5-base: A general-purpose Transformer that can be used to translate from English to German, French, or Romanian.

Explore all available models and find the one that suits you best here.

Using the API

Python
JavaScript
cURL
import requests

API_URL = "https://api-inference.huggingface.co/models/google-t5/t5-base"
headers = {"Authorization": "Bearer hf_***"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.json()
	
output = query({
	"inputs": "Меня зовут Вольфганг и я живу в Берлине",
})

To use the Python client, see huggingface_hub’s package reference.

API specification

Request

Payload
inputs* string The text to translate.
parameters object Additional inference parameters for Translation
        src_lang string The source language of the text. Required for models that can translate from multiple languages.
        tgt_lang string Target language to translate to. Required for models that can translate to multiple languages.
        clean_up_tokenization_spaces boolean Whether to clean up the potential extra spaces in the text output.
        truncation enum Possible values: do_not_truncate, longest_first, only_first, only_second.
        generate_parameters object Additional parametrization of the text generation algorithm.

Some options can be configured by passing headers to the Inference API. Here are the available headers:

Headers
authorization string Authentication header in the form 'Bearer: hf_****' when hf_**** is a personal user access token with Inference API permission. You can generate one from your settings page.
x-use-cache boolean, default to true There is a cache layer on the inference API to speed up requests we have already seen. Most models can use those results as they are deterministic (meaning the outputs will be the same anyway). However, if you use a nondeterministic model, you can set this parameter to prevent the caching mechanism from being used, resulting in a real new query. Read more about caching here.
x-wait-for-model boolean, default to false If the model is not ready, wait for it instead of receiving 503. It limits the number of requests required to get your inference done. It is advised to only set this flag to true after receiving a 503 error, as it will limit hanging in your application to known places. Read more about model availability here.

For more information about Inference API headers, check out the parameters guide.

Response

Body
translation_text string The translated text.
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