compare

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Preload both models
+models = {
+    "moulsot_v0.1_2500": pipeline("automatic-speech-recognition", model="01Yassine/moulsot_v0.1_2500"),
+    "moulsot_v0.2_1000": pipeline("automatic-speech-recognition", model="01Yassine/moulsot_v0.2_1000")
+}
+
+# Adjust generation config for both
+for m in models.values():
+    m.model.generation_config.input_ids = m.model.generation_config.forced_decoder_ids
+    m.model.generation_config.forced_decoder_ids = None
+
+
+def transcribe(audio, selected_model):
+    if audio is None:
+        return "Please record or upload an audio file.", "Please record or upload an audio file."
+    
+    pipe = models[selected_model]
+    other_model = [k for k in models if k != selected_model][0]
+    
+    # Run inference
+    result_selected = pipe(audio)["text"]
+    result_other = models[other_model](audio)["text"]
+
+    return result_selected, result_other
+
+
+title = "🎙️ Moulsot Whisper ASR Comparison"
+description = """
+Compare two fine-tuned Whisper models for **Moroccan ASR**:
+- 🟩 **moulsot_v0.1_2500**
+- 🟦 **moulsot_v0.2_1000**
+
+You can **record** or **upload** an audio sample, then see transcriptions from both models side by side.
+"""
+
+with gr.Blocks(title=title) as demo:
+    gr.Markdown(f"# {title}\n{description}")
+
+    with gr.Row():
+        audio_input = gr.Audio(
+            sources=["microphone", "upload"], 
+            type="filepath", 
+            label="🎤 Record or Upload Audio"
+        )
+        model_choice = gr.Radio(
+            ["moulsot_v0.1_2500", "moulsot_v0.2_1000"],
+            label="Choose Primary Model",
+            value="moulsot_v0.1_2500"
+        )
+
+    transcribe_btn = gr.Button("🚀 Transcribe")
+
+    with gr.Row():
+        output_selected = gr.Textbox(label="🟩 Model 1 Output")
+        output_other = gr.Textbox(label="🟦 Model 2 Output")
+
+    transcribe_btn.click(
+        fn=transcribe,
+        inputs=[audio_input, model_choice],
+        outputs=[output_selected, output_other]
+    )
+
+# For local testing
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+transformers
+torch