Finalized model and inference script

inference.py

@@ -0,0 +1,54 @@
+import os
+import torch
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+from datetime import datetime
+
+# Load model and tokenizer once when the script is initialized
+MODEL_PATH = "."  # Adjust this to match the path in your HF repo
+model = AutoModelForSequenceClassification.from_pretrained(MODEL_PATH)
+tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
+model.eval()
+
+# Mapping for label interpretation
+label_mapping = {0: "Negative", 1: "Positive"}
+
+def predict(inputs):
+    """
+    Function to handle prediction.
+    :param inputs: Dictionary with the text to be analyzed, e.g., {'text': 'I love this movie'}
+    :return: Dictionary with label and confidence score
+    """
+    try:
+        # Extract input text from the dictionary
+        input_text = inputs.get("text")
+        if not input_text:
+            return {"error": "Invalid input, 'text' key is required"}, 400
+
+        # Tokenize the input text
+        tokenized_input = tokenizer(input_text, return_tensors="pt", truncation=True, max_length=512)
+
+        # Perform prediction with the model
+        with torch.no_grad():
+            outputs = model(**tokenized_input)
+            probabilities = torch.nn.functional.softmax(outputs.logits, dim=1)
+            confidence, label_idx = torch.max(probabilities, dim=1)
+            confidence = confidence.item() * 100  # Convert to percentage
+            label = label_mapping[label_idx.item()]
+
+        # Structure the response as a dictionary
+        response = {
+            "data": {
+                "confidence": f"{confidence:.2f}%",
+                "input_text": input_text,
+                "label": label
+            },
+            "model_version": "1.0.0",
+            "status": "success",
+            "timestamp": datetime.now().isoformat()
+        }
+
+        return response
+
+    except Exception as e:
+        # Handle errors gracefully
+        return {"error": str(e)}, 500