# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Chillyblast/Bart_Summarization")
model = AutoModelForSeq2SeqLM.from_pretrained("Chillyblast/Bart_Summarization")

from transformers import pipeline

# Create a pipeline for text summarization
summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)

# Example input for inference
dialogue = input(str("Enter the input:"))
# Perform inference
summary = summarizer(dialogue, max_length=500, min_length=300, do_sample=False)

# Print the summary
print("Summary:", summary[0]['summary_text'])