Add model and Gradio app

app.py

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+import gradio as gr
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import torch
+
+# Load pre-trained model and tokenizer
+model = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased", num_labels=3)
+tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
+
+# Define a function to make predictions using the model
+def predict(text):
+    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
+    with torch.no_grad():
+        outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class = torch.argmax(logits, dim=-1).item()
+    return predicted_class
+
+# Create Gradio interface
+iface = gr.Interface(fn=predict, inputs="text", outputs="text", live=True)
+
+# Launch the Gradio app
+iface.launch()

requirements.txt

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+git add app.py requirements.txt
+git commit -m "Add model and Gradio app"
+git push

requirements.txt.txt

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+git add app.py requirements.txt
+git commit -m "Add model and Gradio app"
+git push