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alsubari
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dytr

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  [![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
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  [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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  [![PyPI version](https://badge.fury.io/py/dytr.svg)](https://badge.fury.io/py/dytr)
 
 
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  **Build dynamic transformers that learn multiple tasks with supports to load and modify pretrained model such as bert.**
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  dytr is a flexible PyTorch library for multi-task learning with transformer architectures. Train multiple tasks sequentially or simultaneously while preserving performance on previous tasks through built-in continual learning techniques.
 
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  [![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
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  [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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  [![PyPI version](https://badge.fury.io/py/dytr.svg)](https://badge.fury.io/py/dytr)
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+ [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://github.com/AAlsubari/dytr/blob/main/dytr_bert_finetune_demo.ipynb)
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  **Build dynamic transformers that learn multiple tasks with supports to load and modify pretrained model such as bert.**
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  dytr is a flexible PyTorch library for multi-task learning with transformer architectures. Train multiple tasks sequentially or simultaneously while preserving performance on previous tasks through built-in continual learning techniques.