# Long-form QA

QA model fine-tuned from ModernBERT-base-nli, supporting long-context processing

A QA model fine-tuned on SQuAD 2.0 dataset based on ModernBERT-large, supporting long-context processing

A query-focused table summarization generation model fine-tuned based on the T5-large architecture, specifically designed for converting tabular data into natural language summaries.

A BART-based model specifically designed for query-oriented table summarization tasks, fine-tuned on the QTSumm dataset

This is a BART-LARGE model fine-tuned for QA tasks on the SQuADv1 dataset, suitable for natural language understanding and generation tasks.

A fine-tuned version of the LONGFORMER-BASE-4096 model on the SQuAD v1 QA dataset, suitable for long-document question answering tasks

This model is a QA system based on the Longformer architecture, fine-tuned on the SQuAD v2 dataset, supporting long text sequences (up to 4096 tokens).