Update README.md

README.md

@@ -36,7 +36,7 @@ This particular model, Bart-Large, is the larger version of the Bart model. It c
 To use this model, you can leverage the Hugging Face [Transformers](https://huggingface.co/transformers/) library. Here's an example of how to use it in Python:
 
 ```python
-from transformers import BartTokenizer, BartForConditionalGeneration
+from transformers import BartTokenizer, BartForConditionalGeneration, pipeline
 
 # Load the model and tokenizer
 model_name = "com3dian/Bart-large-paper2slides-expander"
@@ -49,13 +49,13 @@ input_ids = tokenizer.encode(input_text, return_tensors="pt")
 output = model.generate(input_ids)
 
 # Decode generated summaries
-summary = tokenizer.decode(output[0], skip_special_tokens=True)
-print(summary)
+expanded_text = tokenizer.decode(output[0], skip_special_tokens=True)
+print(expanded_text)
 
 # Or using the pipeline API
-summarizer = pipeline("summarization", model=model_name)
-summary = summarizer(text, max_length=50, min_length=30, do_sample=False)
-print(summary)
+expander = pipeline("text2text-generation", model=model_name)
+expanded_text = expander(input_text, max_length=50, min_length=30, do_sample=False)
+print(expanded_text)
 ```
 
 Ensure you have the `transformers` library installed before running the code. You can install it using `pip`: