Create app.py

app.py

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+import torch
+import gradio as gr
+from sentence_transformers import SentenceTransformer
+from safetensors.torch import load_file
+import torch.nn as nn
+
+# Define the model class (same as in the training script)
+class Magical1Sun(nn.Module):
+    def __init__(self, num_classes, dropout_rate=0.1):
+        super(Magical1Sun, self).__init__()
+        self.sentence_transformer = SentenceTransformer('all-MiniLM-L12-v2')
+        self.dropout = nn.Dropout(dropout_rate)
+        self.classifier = nn.Sequential(
+            nn.Linear(384, 256),
+            nn.ReLU(),
+            nn.Dropout(dropout_rate),
+            nn.Linear(256, num_classes)
+        )
+
+    def forward(self, text):
+        embeddings = self.sentence_transformer.encode(text, convert_to_tensor=True)
+        embeddings = self.dropout(embeddings)
+        return self.classifier(embeddings)
+
+# Load the trained model
+def load_model(model_path):
+    model = Magical1Sun(num_classes=2)
+    state_dict = load_file(model_path)
+    model.load_state_dict(state_dict)
+    model.eval()
+    return model
+
+# Prediction function
+def predict(text):
+    with torch.no_grad():
+        output = model(text)
+        probabilities = torch.softmax(output, dim=0)
+        positive_prob = probabilities[1].item()
+        negative_prob = probabilities[0].item()
+        prediction = "Positive" if positive_prob > negative_prob else "Negative"
+        confidence = max(positive_prob, negative_prob)
+    return {
+        "Prediction": prediction,
+        "Confidence": f"{confidence:.2%}",
+        "Positive Probability": f"{positive_prob:.2%}",
+        "Negative Probability": f"{negative_prob:.2%}"
+    }
+
+# Load the model (make sure to replace 'path_to_your_model.safetensors' with the actual path)
+model = load_model('magical_1_sun.safetensors')
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Textbox(lines=3, placeholder="Enter text to classify..."),
+    outputs=[
+        gr.Label(num_top_classes=1, label="Prediction"),
+        gr.Label(label="Confidence"),
+        gr.Label(label="Positive Probability"),
+        gr.Label(label="Negative Probability")
+    ],
+    title="Magical-1 Sun Text Classification",
+    description="Enter a text to classify it as positive or negative.",
+    examples=[
+        ["I love this product! It's amazing!"],
+        ["This is terrible. Worst purchase ever."],
+        ["Great experience overall. Would buy again."],
+        ["Never buying again. Complete waste of money."],
+        ["Highly recommended! You won't regret it."]
+    ]
+)
+
+# Launch the app
+if __name__ == "__main__":
+    iface.launch()