Update README.md

README.md

@@ -106,7 +106,25 @@ This project was completed to explore the effectiveness of parameter-efficient f
 
 ### Usage
 
-To use this model, follow these steps:
-1. Log in to Hugging Face:
-   ```bash
-   huggingface-cli login
+usage:
+  - step_1: |
+      Log in to Hugging Face:
+      ```bash
+      huggingface-cli login
+      ```
+  - step_2: |
+      Load the model:
+      ```python
+      from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+      tokenizer = AutoTokenizer.from_pretrained("jamander/Project-Blockbuster")
+      model = AutoModelForSequenceClassification.from_pretrained("jamander/Project-Blockbuster")
+      ```
+  - step_3: |
+      Tokenize and predict:
+      ```python
+      inputs = tokenizer("I loved the movie!", return_tensors="pt", padding=True, truncation=True)
+      outputs = model(**inputs)
+      prediction = torch.argmax(outputs.logits, dim=-1)
+      print("Prediction:", "Positive" if prediction == 1 else "Negative")
+      ```