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import gradio as gr | |
from transformers import WhisperForConditionalGeneration, AutoProcessor | |
model_name = "GiorgiSekhniashvili/whisper-tiny-ka-01" | |
processor = AutoProcessor.from_pretrained(model_name) | |
model = WhisperForConditionalGeneration.from_pretrained(model_name) | |
def predict(audio): | |
sr, waveform = audio | |
input_values = processor(waveform, sampling_rate=16_000, return_tensors="pt") | |
res = model.generate( | |
input_values["input_features"], | |
forced_decoder_ids=forced_decoder_ids, | |
max_new_tokens=448, | |
) | |
return processor.batch_decode(res, skip_special_tokens=True) | |
mic = gr.Audio(source="microphone", type="numpy", label="Speak here...") | |
demo = gr.Interface(predict, mic, "audio") | |
if __name__ == "__main__": | |
demo.launch() | |