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@ -5,6 +5,8 @@ unsupervised and supervised tasks.[^1] These models work well on a variety of
tasks by prepending task-specific prefixes to the input, e.g.: tasks by prepending task-specific prefixes to the input, e.g.:
`translate English to German: …`, `summarize: ….`, etc. `translate English to German: …`, `summarize: ….`, etc.
This example also supports the FLAN-T5 models variants.[^2]
## Setup ## Setup
Download and convert the model: Download and convert the model:
@ -25,7 +27,10 @@ The `<model>` can be any of the following:
| t5-3b | 3 billion | | t5-3b | 3 billion |
| t5-11b | 11 billion | | t5-11b | 11 billion |
It also supports t5 variants, such as `google/flan-t5-small`, `google/flan-t5-base`, etc. The FLAN variants can be specified with the e.g. `google/flan-t5-small`,
`google/flan-t5-base`, etc. See the [Hugging Face
page](https://huggingface.co/docs/transformers/model_doc/flan-t5) for a
complete list of models.
## Generate ## Generate
@ -45,3 +50,4 @@ python t5.py --help
[^1]: For more information on T5 see the [original paper](https://arxiv.org/abs/1910.10683) [^1]: For more information on T5 see the [original paper](https://arxiv.org/abs/1910.10683)
or the [Hugging Face page](https://huggingface.co/docs/transformers/model_doc/t5). or the [Hugging Face page](https://huggingface.co/docs/transformers/model_doc/t5).
[^2]: For more information on FLAN-T5 see the [original paper](https://arxiv.org/abs/2210.11416).