SecBERT is a pretrained language model for cyber security text, trained on a dataset of papers from various sources, including APTnotes, Stucco-Data, and CASIE. The model has its own wordpiece vocabulary, secvocab, and is available in two versions, SecBERT and SecRoBERTa. The model can improve downstream tasks such as NER, text classification, semantic understanding, and Q&A in the cyber security domain.
SecBERT is a pretrained language model for cyber security text, trained on a dataset of papers from various sources, including APTnotes, Stucco-Data, and CASIE. The model has its own wordpiece vocabulary, secvocab, and is available in two versions, SecBERT and SecRoBERTa. The model can improve downstream tasks such as NER, text classification, semantic understanding, and Q&A in the cyber security domain.
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/jackaduma/SecBERT'
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
}
}
webhook
fileThe webhook to call when inference is done, by default you will get the output in the response of your inference request