| from transformers import pipeline | |
| import gradio as gr | |
| pipe = pipeline(model="SharatChandra/whisper-fine-banking-dataset") # change to "your-username/the-name-you-picked" | |
| def transcribe(audio): | |
| text = pipe(audio, generate_kwargs = {"task":"translate", "language":"english"})["text"] | |
| return text | |
| iface = gr.Interface( | |
| fn=transcribe, | |
| inputs=gr.Audio(type="filepath"), | |
| outputs="text", | |
| title="Whisper Medium Bank Domain", | |
| description="Realtime demo for Banking Domain speech recognition using a fine-tuned Whisper medium model.", | |
| ) | |
| iface.launch() |