| from transformers import pipeline | |
| import gradio as gr | |
| import torch | |
| def detect_gpu(): | |
| if not torch.cuda.is_available(): | |
| print("No GPU device found") | |
| exit() | |
| print(f"Found {torch.cuda.device_count()} GPU device(s)") | |
| print(f"Using {torch.cuda.get_device_name(0)}") | |
| detect_gpu() | |
| pipe = pipeline(model="pierrelf/whisper-small-sv", device=0) | |
| def transcribe(audio): | |
| text = pipe(audio)["text"] | |
| return text | |
| iface = gr.Interface( | |
| fn=transcribe, | |
| inputs=gr.Audio(sources=['upload', 'microphone'], type="filepath"), | |
| outputs="text", | |
| title="Whisper Swedish", | |
| description="Realtime demo for Swedish speech recognition using a fine-tuned Whisper small model.", | |
| ) | |
| iface.launch(server_name="0.0.0.0") |