Update app.py

app.py

@@ -1,16 +1,33 @@
-model_path = '/content/drive/My Drive/Bart_samsum'
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-from transformers import pipeline
+tokenizer = AutoTokenizer.from_pretrained("Chillyblast/Bart_Summarization")
+model = AutoModelForSeq2SeqLM.from_pretrained("Chillyblast/Bart_Summarization")
 
-# Load the tokenizer and model from the specified path
-tokenizer = AutoTokenizer.from_pretrained(model_path)
-model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
+from transformers import pipeline
 
 # Create a pipeline for text summarization
 summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)
 
 # Example input for inference
-
+dialogue=
+'''
+Hannah: Hey, do you have Betty's number?
+Amanda: Lemme check
+Hannah: <file_gif>
+Amanda: Sorry, can't find it.
+Amanda: Ask Larry
+Amanda: He called her last time we were at the park together
+Hannah: I don't know him well
+Hannah: <file_gif>
+Amanda: Don't be shy, he's very nice
+Hannah: If you say so..
+Hannah: I'd rather you texted him
+Amanda: Just text him 🙂
+Hannah: Urgh.. Alright
+Hannah: Bye
+Amanda: Bye bye
+'''
 # Perform inference
 summary = summarizer(dialogue, max_length=500, min_length=300, do_sample=False)