---
title: transformer_qa
canonical_url: "https://www.modelscope.cn/models/LLM-Research/transformer_qa"
md_url: "https://www.modelscope.cn/models/LLM-Research/transformer_qa.md"
repository: LLM-Research/transformer_qa
last_updated: 2024-09-08
pipeline_tag: question-answering
tasks:
  - question-answering
library_name:
  - pytorch
frameworks:
  - pytorch
language:
  - en
downloads: 2733
stars: 0
tags:
  - allennlp
  - question-answering
---

# transformer_qa

> transformer_qa - LLM-Research 在 ModelScope 开源的模型。A reading comprehension model patterned after the proposed model in Devlin et al, with improvements borrowed from the SQuAD model in the transformers project The model implements a reading comprehension model…

- **Repository**: LLM-Research/transformer_qa
- **Tasks**: question-answering
- **Tags**: allennlp, question-answering
- **Downloads**: 2733
- **Stars**: 0
- **Last updated**: 2024-09-08

Source: https://www.modelscope.cn/models/LLM-Research/transformer_qa

---

A reading comprehension model patterned after the proposed model in Devlin et al, with improvements borrowed from the SQuAD model in the transformers project
The model implements a reading comprehension model patterned after the proposed model in BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (Devlin et al, 2018), with improvements borrowed from the SQuAD model in the transformers project. It predicts start tokens and end tokens with a linear layer on top of word piece embeddings.