hfl/chinese-roberta-wwm-ext
We present Chinese pre-trained BERT with Whole Word Masking, which is an extension of the original BERT model tailored for Chinese natural language processing tasks. This variant uses whole word masking instead of subword tokenization to improve performance on out-of-vocabulary words and enhance language understanding capabilities.
We present Chinese pre-trained BERT with Whole Word Masking, which is an extension of the original BERT model tailored for Chinese natural language processing tasks. This variant uses whole word masking instead of subword tokenization to improve performance on out-of-vocabulary words and enhance language understanding capabilities.
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/hfl/chinese-roberta-wwm-ext'
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
