| |
| import gradio as gr |
| from transformers import pipeline |
| import spaces |
|
|
| @spaces.GPU |
| def load_model(): |
| return pipeline( |
| "automatic-speech-recognition", |
| model="palli23/whisper-small-sam_spjall", |
| device=0, |
| token=os.getenv("HF_TOKEN") |
| ) |
|
|
| |
| asr = load_model() |
|
|
| def transcribe(audio): |
| if not audio: |
| return "Hladdu upp hljóðskrá" |
| try: |
| result = asr(audio) |
| return result["text"] |
| except Exception as e: |
| return f"Villa: {str(e)}" |
|
|
| with gr.Blocks() as demo: |
| gr.Markdown("# Íslenskt ASR – Virkar á A100") |
| gr.Markdown("**Whisper-small · ~4–5 % WER · Keyrir á GPU**") |
| |
| audio = gr.Audio(type="filepath", label="Hladdu upp .mp3 / .wav") |
| btn = gr.Button("Transcribe", variant="primary") |
| out = gr.Textbox(lines=20, label="Útskrift") |
| |
| btn.click(transcribe, audio, out) |
|
|
| demo.launch(auth=("beta", "beta2025")) |