Update README.md

README.md

@@ -28,11 +28,24 @@ pip install transformers
 
 You can easily load the pre-trained model for sentiment analysis using Hugging Face's AutoModelForSequenceClassification.
 
-```bash
+```python
 from transformers import DistilBertForSequenceClassification, DistilBertTokenizerFast
+import torch
 
-model_name = "ongaunjie/distilbert-cloths-sentiment"  # Replace with a valid model name from Hugging Face's model hub
+model_name = "ongaunjie/distilbert-cloths-sentiment" 
 tokenizer = DistilBertTokenizerFast.from_pretrained(model_name)
 model = DistilBertForSequenceClassification.from_pretrained(model_name)
 
+## Inference
+You can use this model to perform sentiment analysis on text. Here's an example of how to do it in Python:
+
+```python
+review = "This dress is amazing, I love it!"
+inputs = tokenizer.encode(review, return_tensors="pt")
+with torch.no_grad():
+    outputs = model(inputs)
+predicted_class = int(torch.argmax(outputs.logits))
+
+
+