bert-base-cased
A transformer-based language model developed by Google Research that achieved state-of-the-art results on a wide range of NLP tasks. The model was pre-trained on a large corpus of English text, including BookCorpus and English Wikipedia, using a masked language modeling objective. Fine-tuned versions of the model are available for various downstream tasks, and the model has been shown to achieve excellent results on tasks such as question answering, sentiment analysis, and named entity recognition.
A transformer-based language model developed by Google Research that achieved state-of-the-art results on a wide range of NLP tasks. The model was pre-trained on a large corpus of English text, including BookCorpus and English Wikipedia, using a masked language modeling objective. Fine-tuned versions of the model are available for various downstream tasks, and the model has been shown to achieve excellent results on tasks such as question answering, sentiment analysis, and named entity recognition.
HTTP/cURL API
You can use cURL or any other http client to run inferences:
curl -X POST \
-d '{"input": "Where is my [MASK]?"}' \
-H "Authorization: bearer $DEEPINFRA_TOKEN" \
-H 'Content-Type: application/json' \
'https://api.deepinfra.com/v1/inference/bert-base-cased'
which will give you back something similar to:
{
"results": [
{
"sequence": "where is my father?",
"score": 0.08898820728063583,
"token": 2269,
"token_str": "father"
},
{
"sequence": "where is my mother?",
"score": 0.07864926755428314,
"token": 2388,
"token_str": "mother"
}
],
"request_id": null,
"inference_status": {
"status": "unknown",
"runtime_ms": 0,
"cost": 0.0,
"tokens_generated": 0,
"tokens_input": 0
}
}
Input fields
webhookfile
The webhook to call when inference is done, by default you will get the output in the response of your inference request
