# High-precision QA

A BERT model fine-tuned for extractive question-answering tasks on Turkish legal texts, capable of extracting relevant segments from legal clauses to answer questions.

This model is a Q&A dataset for the medical field, primarily designed to support accurate responses to medical-related questions.

This model is a Hungarian question-answering model fine-tuned on the milqa dataset based on deepset/xlm-roberta-large-squad2, supporting handling cases with no answers.

Electra-qa is a Q&A model based on the ELECTRA architecture, suitable for question-answering tasks.

A question-answering model fine-tuned on SpanBERT/spanbert-base-cased, suitable for reading comprehension tasks

An open-domain question answering model trained on the complete Natural Questions (NQ) dataset, capable of answering various factual questions

A QA model fine-tuned on the Persian QA dataset PQuAD based on the XLM-RoBERTA multilingual pretrained model

This model is a fine-tuned version of DeBERTa-base on the SQuAD question answering dataset, designed for automatic question answering tasks

This model is a question-answering model based on DeBERTa-base, fine-tuned on the SQuAD1 dataset and further fine-tuned on the adversarial_qa dataset.

A question-answering model fine-tuned on the SQuAD dataset based on RoBERTa-base

This model is a question-answering model fine-tuned on the SQuAD 2.0 dataset based on RoBERTa-base, excelling in reading comprehension tasks.

A Q&A model fine-tuned on the SQuAD 2.0 dataset based on the RoBERTa-base model

This model is a fine-tuned version of the RoBERTa large model using the CUAD legal contract dataset, specifically designed for legal contract review 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 question-answering system fine-tuned on the squad_v2 dataset based on PubMedBERT, suitable for medical domain Q&A tasks.

A Q&A system model fine-tuned on the SQuAD1.1 dataset based on the bert-base-uncased model

A Q&A model fine-tuned on the squad_v2 dataset based on the xlm-roberta-large model