| from transformers import pipeline | |
| import gradio as gr | |
| pipe = pipeline(model="LadislavVasina1/whisper-base-cs-cv11-timestetch02-gain01-pitch02-gaussian02-lowpass01") | |
| def transcribe(audio): | |
| text = pipe(audio)["text"] | |
| return text | |
| gradio_app = gr.Interface( | |
| fn=transcribe, | |
| inputs=gr.Audio(type="filepath"), | |
| outputs="text", | |
| title="Whisper Base CS", | |
| #description="Realtime demo for Czech speech recognition using a fine-tuned Whisper base model.", | |
| ) | |
| if __name__ == "__main__": | |
| gradio_app.launch() |