Update README.md

README.md

@@ -23,5 +23,20 @@ base_model:
   - Trained over 3 epochs with learning rate adjustments and evaluation every 500 steps.
 
 ## Usage
+import torch
 
+# Check if a GPU is available
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+# Move the model to the device
+model.to(device)
+input_text = "tell me joke with bbc"
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+input_ids = input_ids.to(device)
+
+# Generate summary
+output = model.generate(input_ids, max_length=50, num_beams=4, early_stopping=True)
+generated_summary = tokenizer.decode(output[0], skip_special_tokens=True)
+
+print(generated_summary)
 To use this model for text generation: