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  # Python T5 base model
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- Pre-trained model on CodeSearchNet Python dataset using a span-masking objective. The training objective and model were introduced in this paper and first released in this repository. PyT5 model used git-t5 framework build on top of JAX/Flax to pre-train the model on a TPU v3-8 node.
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  # How to use
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  You can use this model to denoise span-masked sequences. Note, that you'll need to add some boilerplate code for adding the noise to your sequences.
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  Add the following code for encoding an input text:
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  ```python
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  from typing import Dict, Optional, Tuple
 
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  # Python T5 base model
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+ Pre-trained model on CodeSearchNet Python dataset using a span-masking objective. The training objective and model were introduced in [this paper](https://arxiv.org/pdf/1910.10683.pdf) and first released in [this repository](https://github.com/google-research/text-to-text-transfer-transformer). PyT5 model used [git-t5](https://github.com/formermagic/git-t5) framework built on top of JAX/Flax to pre-train the model on a TPU v3-8 node.
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  # How to use
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  You can use this model to denoise span-masked sequences. Note, that you'll need to add some boilerplate code for adding the noise to your sequences.
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+ First, install the `git-t5` pip package:
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+ ```shell
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+ > pip install git-t5
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+ ```
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+
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  Add the following code for encoding an input text:
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  ```python
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  from typing import Dict, Optional, Tuple