71 lines
3.0 KiB
Markdown
71 lines
3.0 KiB
Markdown
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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# T5v1.1
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## Overview
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T5v1.1 was released in the [google-research/text-to-text-transfer-transformer](https://github.com/google-research/text-to-text-transfer-transformer/blob/main/released_checkpoints.md#t511)
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repository by Colin Raffel et al. It's an improved version of the original T5 model.
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This model was contributed by [patrickvonplaten](https://huggingface.co/patrickvonplaten). The original code can be
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found [here](https://github.com/google-research/text-to-text-transfer-transformer/blob/main/released_checkpoints.md#t511).
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## Usage tips
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One can directly plug in the weights of T5v1.1 into a T5 model, like so:
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```python
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>>> from transformers import T5ForConditionalGeneration
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>>> model = T5ForConditionalGeneration.from_pretrained("google/t5-v1_1-base")
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```
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T5 Version 1.1 includes the following improvements compared to the original T5 model:
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- GEGLU activation in the feed-forward hidden layer, rather than ReLU. See [this paper](https://arxiv.org/abs/2002.05202).
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- Dropout was turned off in pre-training (quality win). Dropout should be re-enabled during fine-tuning.
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- Pre-trained on C4 only without mixing in the downstream tasks.
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- No parameter sharing between the embedding and classifier layer.
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- "xl" and "xxl" replace "3B" and "11B". The model shapes are a bit different - larger `d_model` and smaller
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`num_heads` and `d_ff`.
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Note: T5 Version 1.1 was only pre-trained on [C4](https://huggingface.co/datasets/c4) excluding any supervised
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training. Therefore, this model has to be fine-tuned before it is usable on a downstream task, unlike the original T5
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model. Since t5v1.1 was pre-trained unsupervisedly, there's no real advantage to using a task prefix during single-task
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fine-tuning. If you are doing multi-task fine-tuning, you should use a prefix.
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Google has released the following variants:
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- [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small)
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- [google/t5-v1_1-base](https://huggingface.co/google/t5-v1_1-base)
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- [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large)
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- [google/t5-v1_1-xl](https://huggingface.co/google/t5-v1_1-xl)
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- [google/t5-v1_1-xxl](https://huggingface.co/google/t5-v1_1-xxl).
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<Tip>
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Refer to [T5's documentation page](t5) for all API reference, tips, code examples and notebooks.
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</Tip> |