Roberta
RoBERTa is a transformers model pretrained on a large corpus of English data in a self-supervised fashion. It was trained on English language using a masked language modeling (MLM) objective. It was introduced in this paper and first released in this repository. This model is case-sensitive: it makes a difference between english and English. We currently have the following Roberta 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:
- Roberta Large:
roberta-large
Once you’ve deployed a Roberta 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/roberta-large-webhook/predict' \
--header 'Authorization: <API_KEY>' \
--header 'Content-Type: application/json' \
--data-raw '{
"prompt": "<mask> is the capital of France"
}'
This is the Cerebrium API key used to authenticate your request. You can get it from your Cerebrium dashboard.
The prompt you would like Roberta to process. Please make sure that you include the <mask> keyword.
"run_id": "<UUID_STRING>",
"run_time_ms": 251,
"message": "Successfully generated text",
"result": [{'sequence': "<s>Paris</s>",
'score': 0.3317350447177887,
'token': 2943,
'token_str': 'Paris'},
{'sequence': "<s>Nice</s>",
'score': 0.14171843230724335,
'token': 2734,
'token_str': 'Nice'},
...
]`
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 Roberta
curl --location --request POST 'https://run.cerebrium.ai/roberta-large-webhook/predict' \
--header 'Authorization: <API_KEY>' \
--header 'Content-Type: application/json' \
--data-raw '{
"prompt": "<mask> is the capital of France"
}'
"run_id": "<UUID_STRING>",
"run_time_ms": 251,
"message": "Successfully generated text",
"result": [{'sequence': "<s>Paris</s>",
'score': 0.3317350447177887,
'token': 2943,
'token_str': 'Paris'},
{'sequence': "<s>Nice</s>",
'score': 0.14171843230724335,
'token': 2734,
'token_str': 'Nice'},
...
]`