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<!-- # Model Card for Model ID --> |
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<!-- Provide a quick summary of what the model is/does. --> |
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<!-- This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). --> |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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Longformer-Encoder-Decoder (LED) model is designed to address the challenge of summarizing lengthy English texts, particularly legal documents. Utilizing a local-global attention mechanism, LED is capable of handling longer input sequences efficiently, making it highly suitable for legal document summarization tasks. |
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## Citation |
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**BibTeX:** |
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``` |
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@misc{duc2023led, |
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author = {Chu Đình Đức}, |
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title = {Longformer-Encoder-Decoder for Legal Document Summarization}, |
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year = {2023}, |
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} |
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``` |
