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实验环境:python3.5 paddlepaddle-gpu==1.0.0.post87 ubuntu16.04 GPU 使用 两个1080Ti
执行 `sh run.sh --train --pass_num 10` 时, 在执行到`2018-12-17 11:15:38,728 - brc - INFO - Training the model...
` 时 报错如下
```bash…
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### Pandas version checks
- [X] I have checked that the issue still exists on the latest versions of the docs on `main` [here](https://pandas.pydata.org/docs/dev/)
### Location of the documentation…
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Dear Dr. Sean,
I hope this message finds you well. I am writing to express my admiration for your recent publication in Current Biology titled "High viral abundance and low diversity are associated…
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### Type of Enhancement
Server Backend
### Describe the Feature/Enhancement
Audiobookshelf currently supports various audiobook and ebook formats. This feature request is to enable support fo…
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### Is there an existing feature request for this?
- [X] I have searched the existing feature requests
### What feature would you like to see?
## New Feature: Reading Mode
### Feature Descriptio…
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MultiRC is one of the tasks of the [SuperGLUE](https://super.gluebenchmark.com) benchmark. The task is to re-trace the steps of Facebook's RoBERTa paper (https://arxiv.org/pdf/1907.11692.pdf) and buil…
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## 一言でいうと
複数根拠文にまたがる推論が必要な質問(日光は日本にある/日光には猿がいる=日本に猿がいる、等)について、一度に回答せず一つ一つの質問に分解して答えるという手法。個別質問への分解は少量のアノテーションで学習し(400件)、入力文を元にどの個別質問の回答が正答かを予測する。
![image](https://user-images.githubusercontent.c…
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## 一言でいうと
Microsoftが公開した質問応答のデータセット(10万件)。質問/回答が、人間のものである点が特徴(Bing=検索エンジンへの入力なのでどこまで質問っぽいかは要確認)。回答はBingの検索結果から抜粋して作成。
### 論文リンク
https://arxiv.org/pdf/1611.09268v1.pdf
### 著者/所属機関
Tri Ng…
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Hi all, the Bert paper discusses how to adopt this model for Question Answering/Reading Comprehension tasks like SQUAD where you just combine the passage and question into a single packed sequence and…
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1. 약 61,860 개 영어의 SQuAD, MS MARCO 문서와 질문 쌍에 대해 특정한 문장을 넣을 경우, 문장에 대한 질문을 생성하는 Question Generation 모델.
2. Learning to Ask: Neural Question Generation for Reading Comprehension
3. Question Generation …