Update abstractive_summarization.py

abstractive_summarization.py

@@ -1,10 +1,15 @@
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 
+# Load the fine-tuned BART tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("EE21/BART-ToSSimplify")
+model = AutoModelForSeq2SeqLM.from_pretrained("EE21/BART-ToSSimplify")
+
 # Function to summarize using the fine-tuned BART model
 def summarize_with_bart_ft(input_text):
-    pipe_bart_ft = pipeline("summarization", model="EE21/BART-ToSSimplify")
-    summary = pipe_bart_ft(input_text, max_length=300, min_length=100, num_beams=1, early_stopping=False, length_penalty=1)
-    return summary[0]['summary_text']
+    inputs = tokenizer.encode("summarize: " + input_text, return_tensors="pt", max_length=1024, truncation=True)
+    summary_ids = model.generate(inputs, max_length=300, min_length=100, num_beams=1, early_stopping=False, length_penalty=1)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=False)
+    return summary
 
 # Function to summarize using BART-large-cnn
 def summarize_with_bart_cnn(input_text):