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| # prompt: give me inference of my code | |
| # Assuming 'model_path' is the path to your saved model | |
| model_path = '/content/drive/MyDrive/ahsan' | |
| # 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 = """ | |
| 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=50, min_length=20, length_penalty=2.0) | |
| # Print the generated summary | |
| print("Summary:", summary[0]['summary_text']) | |