| **Examples** | |
| - The `old` folder contains all the old examples that works with AraBERTv1 | |
| - For Question Answering check the `question-answering` folder, and these 2 notebooks: | |
| - Arabic TyDiQA: [![Open In Colab][COLAB]](https://colab.research.google.com/drive/1hik0L_Dxg6WwJFcDPP1v74motSkst4gE?usp=sharing) | |
| - Arabic-SQuAD + ARCD: [![Open In Colab][COLAB]](https://colab.research.google.com/drive/1eIoVxKZP9KWLumkHHrfmU8Vtb-BLWiVD?usp=sharing) | |
| - Text generation with AraGPT2 [![Open In Colab][COLAB]](https://colab.research.google.com/drive/1T5xKRAtKeuUmmokyThvkK8pulHw02CoK?usp=sharing) | |
| - Zero-Shot Question Answering and Translation with AraGPT2-mega [![Open In Colab][COLAB]](https://colab.research.google.com/drive/1NBghhl2laYZ9jHPKYWTLLUM8R1LePdU6?usp=sharing) | |
| - Text-classification/Sentiment Analysis with Hyper Parameter tuning [![Open In Colab][COLAB]](https://colab.research.google.com/drive/1P9iQHtUH5KUbTVtp8B4-AopZzEEPE0lw?usp=sharing) | |
| - NER with ANERCorp-CamelSplits and Hyper Parameter tuning [![Open In Colab][COLAB]](https://colab.research.google.com/drive/128wX6r_Nz-2LZ_lROeWjWS_yTi96KR7J?usp=sharing) | |
| - Extract word embeddings from sentences using the Transformers Library [![Open In Colab][COLAB]](https://colab.research.google.com/drive/1Xk8IGcwGTr-YNlB6lhl8jYdIU_M7Mcjx?usp=sharing) | |
| [COLAB]: https://colab.research.google.com/assets/colab-badge.svg |