Create app.py

app.py

@@ -0,0 +1,18 @@
+from transformers import pipeline
+import gradio as gr
+
+pipe = pipeline(model="NS-Y/whisper-tiny-he-ex", generate_kwargs = {"language":"<|he|>","task": "transcribe"})  # change to "your-username/the-name-you-picked"
+
+def transcribe(audio):
+    text = pipe(audio)["text"]
+    return text
+
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(source="upload", type="filepath"),
+    outputs="text",
+    title="NS-Y/whisper-tiny-he-ex",
+    description="Realtime demo for Hebrew speech recognition using a fine-tuned NS-Y/whisper-tiny-he-ex.",
+)
+
+iface.launch(share=True)