Create model.py

model.py

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+from transformers import AutoModelForSequenceClassification,AutoTokenizer
+#import tensorflow as tf
+#print(tf.__version__)
+# replace "path/to/model/directory" with the path to the directory containing the model files
+tokenizer = AutoTokenizer.from_pretrained("ALANZI/imamu_arabic_sentimentAnalysis")
+model = AutoModelForSequenceClassification.from_pretrained("ALANZI/imamu_arabic_sentimentAnalysis")
+
+
+def predict_sentiment(text):
+    # Tokenize input text
+    inputs = tokenizer(text, return_tensors="pt")
+
+    # Pass the tokenized inputs through the model
+    outputs = model(**inputs)
+
+    # Get predicted sentiment
+    predictions = outputs.logits.argmax(dim=1)
+    sentiment = "Negative" if predictions.item() == 1 else "Positive"
+
+    return sentiment