Add .ipynb_checkpoints to .gitignore

app.py

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+import torch
+import gradio as gr
+import torchaudio
+from transformers import AutoModel, AutoProcessor
+from quanto import qint8, quantize, freeze
+
+# Load and quantize the model
+model_name = "cdactvm/w2v-bert-punjabi"
+model = AutoModel.from_pretrained(model_name)
+processor = AutoProcessor.from_pretrained(model_name)
+
+# Quantization
+quantize(model, weights=qint8, activations=None)
+freeze(model)
+
+# Audio transcription function
+def transcribe(audio):
+    waveform, sample_rate = torchaudio.load(audio)
+
+    # Ensure 16kHz sample rate
+    if sample_rate != 16000:
+        waveform = torchaudio.transforms.Resample(sample_rate, 16000)(waveform)
+
+    # Process audio
+    inputs = processor(waveform.squeeze(0), sampling_rate=16000, return_tensors="pt")
+
+    # Run inference
+    with torch.no_grad():
+        logits = model(**inputs).logits
+
+    # Decode transcription
+    predicted_ids = torch.argmax(logits, dim=-1)
+    transcription = processor.batch_decode(predicted_ids)[0]
+    
+    return transcription
+
+# Gradio UI
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(source="upload", type="filepath"),
+    outputs="text",
+    title="Punjabi Speech Recognition",
+    description="Upload an audio file and get a Punjabi transcription using a quantized model.",
+)
+
+iface.launch()

requirements.txt

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+torch
+transformers
+torchaudio
+quanto
+gradio