Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load the fine-tuned model and tokenizer into a pipeline
+#model_path = "model"  # Replace with your actual model path
+sentiment_pipeline = pipeline("sentiment-analysis", model="Walid-Ahmed/arabic-sentiment-model", tokenizer=model_path)
+
+
+# Define label mapping
+label_map = {
+    "LABEL_0": "Negative",
+    "LABEL_1": "Positive"
+}
+
+# Define a function to process the input and return the sentiment analysis result
+def analyze_sentiment(text):
+    result = sentiment_pipeline(text)
+    # Extract the label and confidence score from the result
+    label = result[0]['label']
+    score = result[0]['score']
+    return f"Sentiment: {label}, Confidence: {score:.2f}"
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=analyze_sentiment,  # Function to process input
+    inputs="text",         # Text input field
+    outputs="text",        # Text output field
+    title="Arabic Sentiment Analysis",
+    description="Enter an Arabic sentence and get the sentiment (positive or negative).",
+    examples=[["هذا المنتج رائع جدا"], ["هذا المنتج سيء للغاية"]]
+)
+
+# Launch the Gradio app
+interface.launch()