aubmindlab/bert-base-arabertv02
An Arabic pretrained language model based on Google's BERT architecture, with two versions: AraBERTv1 and AraBERTv2. It uses the same BERT-Base configuration and is trained on a large dataset of 200 million words, including OSCAR-unshuffled, Arabic Wikipedia, and Assafir news articles. The model is available in TensorFlow 1.x and Hugging Face models repository.
An Arabic pretrained language model based on Google's BERT architecture, with two versions: AraBERTv1 and AraBERTv2. It uses the same BERT-Base configuration and is trained on a large dataset of 200 million words, including OSCAR-unshuffled, Arabic Wikipedia, and Assafir news articles. The model is available in TensorFlow 1.x and Hugging Face models repository.
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/aubmindlab/bert-base-arabertv02'
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
