Update app.py

app.py

@@ -1,7 +1,7 @@
-from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
-from flask import Flask, request, jsonify
+# prompt: give me inference of my code
+
 # Assuming 'model_path' is the path to your saved model
-model_path = '/content/drive/My Drive/T5_samsum'
+model_path = '/content/drive/MyDrive/ahsan'
 
 # Load the fine-tuned model and tokenizer
 model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
@@ -11,12 +11,19 @@ summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)
 
 # Input text for summarization
 input_text = """
-Your long text that you want to summarize goes here.
-It can be a document or any lengthy content you need to condense.
-"""
 
+The logjam coincided with the Bohra community leader’s arrival at the Sindh Governor House.
+
+In an alert posted at 7:38pm, the Karachi Traffic Police s aid Ziauddin Ahmed road going towards PIDC Chowk to the State Life Building was opened for one-track traffic coming and going.
+
+Sindh Chief Minister Murad Ali Shah took notice of the traffic situation and ordered the administration, district and traffic police to open roads for traffic.
+
+He also instructed that traffic management in the city be improved and further directed that the CM Secretariat be reported to after the opening of roads.
+
+
+"""
 # Perform summarization
-summary = summarizer(input_text, max_length=150, min_length=50, length_penalty=2.0)
+summary = summarizer(input_text, max_length=50, min_length=20, length_penalty=2.0)
 
 # Print the generated summary
 print("Summary:", summary[0]['summary_text'])