Longformer is a transformer-based deep learning model developed by Allen Institute for AI (AI2), designed to efficiently process long documents that exceed the typical input limits of standard transformers like BERT. By introducing a novel sliding window attention mechanism combined with global attention tokens, Longformer significantly reduces computation cost while retaining strong performance on natural language processing (NLP) tasks such as classification, summarization, and question answering.

Features of Longformer:

• Efficiently handles long sequences up to 4,096 tokens (and beyond in custom setups).
• Introduces sliding window attention for linear scaling and global attention for task-specific tokens.
• Supports integration with Python libraries like Hugging Face Transformers for model inference and fine-tuning.
• Well-suited for processing long-form text in domains such as legal, scientific, and medical analysis.
• Compatible with both CPU and GPU computation for scalable workloads.
• Open-source, actively maintained, and widely used in NLP research and real-world applications.

To check the installed Longformer setup and Transformers version on your system, run:

# sudo su
# sudo apt update
# cd /opt/longformer
# source venv/bin/activate
# python -c 'import transformers; print("Transformers version:", transformers.__version__)'

Disclaimer: Longformer is accessible via the Hugging Face Transformers library and is maintained by the Allen Institute for AI (AI2) and the open-source community. Users are responsible for its correct usage in their specific applications. Always refer to the official Hugging Face documentation and Longformer research papers for the most accurate and up-to-date information.