Create app.py

app.py

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+import gradio as gr
+from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
+import torch
+import librosa
+
+# Model details
+models = {
+    "m3hrdadfi/wav2vec2-large-xlsr-persian-v3": None,
+    "jonatasgrosman/wav2vec2-large-xlsr-53-persian": None,
+    "AlirezaSaei/wav2vec2-large-xlsr-persian-fine-tuned": None
+}
+
+# Load models and processors
+def load_model(model_name):
+    model = Wav2Vec2ForCTC.from_pretrained(model_name)
+    processor = Wav2Vec2Processor.from_pretrained(model_name)
+    return model, processor
+
+def transcribe(audio, model_name):
+    if models[model_name] is None:
+        models[model_name] = load_model(model_name)
+    model, processor = models[model_name]
+
+    audio_data, _ = librosa.load(audio, sr=16000)
+    input_values = processor(audio_data, sampling_rate=16000, return_tensors="pt", padding=True).input_values
+
+    with torch.no_grad():
+        logits = model(input_values).logits
+
+    predicted_ids = torch.argmax(logits, dim=-1)
+    transcription = processor.batch_decode(predicted_ids)[0]
+    return transcription
+
+# Gradio app
+with gr.Blocks(theme="compact") as demo:
+    gr.Markdown("""
+    <h1 style="color: #4CAF50; text-align: center;">Persian Speech-to-Text Models</h1>
+    <p style="text-align: center;">Test the best Persian STT models in one place!</p>
+    """)
+
+    with gr.Row():
+        audio_input = gr.Audio(source="upload", type="filepath", label="Upload your audio file")
+        model_dropdown = gr.Dropdown(
+            choices=list(models.keys()),
+            label="Select Model",
+            value="m3hrdadfi/wav2vec2-large-xlsr-persian-v3"
+        )
+
+    output_text = gr.Textbox(label="Transcription", lines=5, placeholder="The transcription will appear here...")
+
+    transcribe_button = gr.Button("Transcribe", variant="primary")
+
+    transcribe_button.click(
+        fn=transcribe,
+        inputs=[audio_input, model_dropdown],
+        outputs=output_text
+    )
+
+    gr.Markdown("""
+    <footer style="text-align: center; margin-top: 20px;">
+        <p>Created with ❤️ using Gradio and Hugging Face</p>
+    </footer>
+    """)
+
+demo.launch()