bert-base-uncased
A transformers model pretrained on a large corpus of English data in a self-supervised fashion. It was trained on BookCorpus, a dataset consisting of 11,038 unpublished books, and English Wikipedia, excluding lists, tables, and headers. The model learns an inner representation of the English language that can then be used to extract features useful for downstream tasks.
A transformers model pretrained on a large corpus of English data in a self-supervised fashion. It was trained on BookCorpus, a dataset consisting of 11,038 unpublished books, and English Wikipedia, excluding lists, tables, and headers. The model learns an inner representation of the English language that can then be used to extract features useful for downstream tasks.
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-uncased'
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
