update

abstractive_model.py

@@ -1,7 +1,10 @@
-from transformers import pipeline
-import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-def summarize_with_bart(text):
-    pipe = pipeline("text2text-generation", model="EE21/Fine-tuned-BART-ToS-Summarization")
-    summary = pipe(text, max_length=130, min_length=30, do_sample=False)[0]['generated_text']
+tokenizer = AutoTokenizer.from_pretrained("EE21/Fine-tuned-BART-ToS-Summarization")
+model = AutoModelForSeq2SeqLM.from_pretrained("EE21/Fine-tuned-BART-ToS-Summarization")
+
+def summarize_with_bart(input_text):
+    inputs = tokenizer.encode("summarize: " + input_text, return_tensors="pt", max_length=1024, truncation=True)
+    summary_ids = model.generate(inputs, max_length=150, min_length=40, length_penalty=2.0, num_beams=4, early_stopping=True)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
     return summary