| import gradio as gr | |
| import whisperx | |
| import whisper | |
| import torch | |
| import spaces | |
| def transcribe(audio_file): | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| # Transcribe with original Whisper | |
| model = whisper.load_model("medium", device) | |
| result = model.transcribe(audio_file) | |
| return result | |
| inputs = gr.Audio(sources="upload", type="filepath") | |
| outputs = gr.JSON() | |
| gr.Interface(fn=transcribe, inputs=inputs, outputs=outputs).launch() | |