app.py

app.py

@@ -1,7 +1,24 @@
+from transformers import pipeline
 import gradio as gr
+from huggingface_hub import login
+with open("../../token.txt", "r") as file:
+    token = file.readline().strip()
 
-def greet(name):
-    return "Hello " + name + "!!"
+login(token=token, add_to_git_credential=True)
+
+
+pipe = pipeline(model="dacavi/whisper-small-hi")  # 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(sources="microphone", type="filepath"),
+    outputs="text",
+    title="Whisper Small Hindi",
+    description="Realtime demo for Hindi speech recognition using a fine-tuned Whisper small model.",
+)
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 iface.launch()