openai/whisper-medium
Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. It was trained on 680k hours of labeled data and demonstrates strong abilities to generalize to various datasets and domains without fine-tuning. The model is based on a Transformer encoder-decoder architecture.
Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. It was trained on 680k hours of labeled data and demonstrates strong abilities to generalize to various datasets and domains without fine-tuning. The model is based on a Transformer encoder-decoder architecture.
HTTP/cURL API
You can use cURL or any other http client to run inferences:
curl -X POST \
-H "Authorization: bearer $DEEPINFRA_TOKEN" \
-F audio=@my_voice.mp3 \
'https://api.deepinfra.com/v1/inference/openai/whisper-medium'
which will give you back something similar to:
{
"text": "",
"segments": [
{
"id": 0,
"text": "Hello",
"start": 0.0,
"end": 1.0
},
{
"id": 1,
"text": "World",
"start": 4.0,
"end": 5.0
}
],
"language": "en",
"input_length_ms": 0,
"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
