# Lightweight BART

DistilBART-CNN-12-6 is a lightweight summarization generation model based on the BART architecture, specifically optimized for the CNN/Daily Mail dataset.

A lightweight text summarization model based on the BART architecture, compressing the original model size through knowledge distillation while retaining core summarization capabilities

This model is a text summarization model fine-tuned on the BBC News Summary dataset based on sshleifer/distilbart-cnn-12-6, developed by the Deep Natural Language Processing Course Lab at Politecnico di Torino.

A resume summary generation model fine-tuned based on distilbart-cnn-12-6, performing well on ROUGE metrics

DistilBART is a distilled version of the BART model, focusing on text summarization tasks, significantly improving inference speed while maintaining high performance.

This is a pruned and optimized BART-base model specifically designed for summarization tasks, retaining 53% of the original model's weights.

DistilBART is a distilled version of the BART model, specifically optimized for summarization tasks, significantly reducing model parameters and inference time while maintaining high performance.

This is a pruned and optimized BART-base model, specifically fine-tuned on the CNN/DailyMail dataset for summarization tasks.