Update README.md

README.md

@@ -118,33 +118,6 @@ print(result)
 
 ---
 
-### **2️⃣ Use Model with `AutoModelForSequenceClassification`**
-For **batch processing & lower latency**, use the `AutoModel` API:
-```python
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-import torch
-
-model_name = "Abduuu/ArabReview-Sentiment"
-
-# Load Model & Tokenizer
-model = AutoModelForSequenceClassification.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-# Example Review
-review = "الخدمة كانت بطيئة والطعام غير جيد."
-inputs = tokenizer(review, return_tensors="pt")
-
-# Perform Inference
-with torch.no_grad():
-    logits = model(**inputs).logits
-    prediction = torch.argmax(logits).item()
-
-label_map = {0: "Negative", 1: "Positive"}
-print(f"Predicted Sentiment: {label_map[prediction]}")
-```
-
----
-
 ## **🔬 Model Performance (Real Examples)**
 | Review | Prediction |
 |--------|------------|