Create app.py

app.py

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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...")
+gr.Interface(predict, mic, "audio").launch()
+
+