# High-precision Q&A

A 7B-parameter causal language model compatible with Meta LLaMA 2 architecture, outperforming similar models under 33B in multiple evaluations

This is a Q&A system model trained on the SQuAD dataset, capable of answering questions based on given text.

A RoBERTa-based question answering model specialized in inferring answer text, span, and confidence scores given a question and context.

A Q&A model based on the DeBERTa-v3-large architecture, fine-tuned on the SQuAD 2.0 dataset, capable of handling both answerable and unanswerable questions.

RoBERTa model optimized for the Contract Understanding Atticus Dataset (CUAD) Q&A task, excelling in legal contract review tasks

This model is a Q&A model fine-tuned on the SQuAD2.0 and COVID-QA datasets based on the ALBERT-xxlarge-v2 architecture