Create app.py

app.py

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+
+# Assuming 'model_path' is the path to your saved model
+model_path = '/content/drive/My Drive/T5_samsum'
+
+# Load the fine-tuned model and tokenizer
+model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+
+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.
+"""
+
+# Perform summarization
+summary = summarizer(input_text, max_length=150, min_length=50, length_penalty=2.0)
+
+# Print the generated summary
+print("Summary:", summary[0]['summary_text'])