MT0
It is pretrained on a cross-lingual task mixture (xP3) and the resulting model is capable of cross-lingual generalization to unseen tasks & languages.You can read more here. We currently have the following MT0 models available below however if you would like any others contact support, and we can quickly add it for you. In order to deploy it you can use the identifier below:
- mt0-xxl:
mt0-xxl
Once you’ve deployed a MT0 model, you can supply the endpoint with a prompt. Here’s an example of how to call the deployed endpoint:
Request Parameters
curl --location --request POST 'https://run.cerebrium.ai/mt0-xxl-webhook/predict' \
--header 'Authorization: <API_KEY>' \
--header 'Content-Type: application/json' \
--data-raw '{
"prompt": "Translate from french to English: Je t'aime."
}'
This is the Cerebrium API key used to authenticate your request. You can get it from your Cerebrium dashboard.
The prompt you would like mt0 to process.
{
"run_id": "<UUID_STRING>",
"run_time_ms": 251,
"message": "Successfully generated text",
"result": "I love you"
}
Response Parameters
A unique identifier for the run that you can use to associate prompts with webhook endpoints.
The amount of time in millisecond it took to run your function. This is what you will be billed for.
Whether of not the response was successful
The result generated from mt0
curl --location --request POST 'https://run.cerebrium.ai/mt0-xxl-webhook/predict' \
--header 'Authorization: <API_KEY>' \
--header 'Content-Type: application/json' \
--data-raw '{
"prompt": "Translate from french to English: Je t'aime."
}'
{
"run_id": "<UUID_STRING>",
"run_time_ms": 251,
"message": "Successfully generated text",
"result": "I love you"
}