| # Simple script to check if transformers is installed correctly | |
| try: | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| print("Transformers library is installed correctly!") | |
| # Try loading a small model to verify functionality | |
| tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-cnn") | |
| model = AutoModelForSeq2SeqLM.from_pretrained("facebook/bart-large-cnn") | |
| print("Model loaded successfully!") | |
| # Test a simple summarization | |
| text = "This is a test sentence to check if the summarisation model works correctly. It should be able to process this text and generate a summary." | |
| inputs = tokenizer(text, return_tensors="pt", max_length=1024, truncation=True) | |
| summary_ids = model.generate(inputs["input_ids"], max_length=50, min_length=10, num_beams=4) | |
| summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True) | |
| print(f"Test summary: {summary}") | |
| except ImportError as e: | |
| print(f"Error importing transformers: {e}") | |
| print("Please try reinstalling with: pip install transformers torch") | |
| except Exception as e: | |
| print(f"Error during model loading or inference: {e}") | |