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Update min versions in README and add Flax (#11472)

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* Update min versions in README and add Flax

* Adapt index
This commit is contained in:
Sylvain Gugger
2021-04-28 09:10:06 -04:00
committed by GitHub
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commit 2d27900b5d
2 changed files with 18 additions and 18 deletions
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@@ -1,12 +1,12 @@
Transformers
=======================================================================================================================
State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
State-of-the-art Natural Language Processing for Jax, Pytorch and TensorFlow
🤗 Transformers (formerly known as `pytorch-transformers` and `pytorch-pretrained-bert`) provides general-purpose
architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet...) for Natural Language Understanding (NLU) and Natural
Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between
TensorFlow 2.0 and PyTorch.
Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between Jax,
PyTorch and TensorFlow.
This is the documentation of our repository `transformers <https://github.com/huggingface/transformers>`_.
@@ -43,11 +43,11 @@ Lower compute costs, smaller carbon footprint:
Choose the right framework for every part of a model's lifetime:
- Train state-of-the-art models in 3 lines of code
- Deep interoperability between TensorFlow 2.0 and PyTorch models
- Move a single model between TF2.0/PyTorch frameworks at will
- Deep interoperability between Jax, Pytorch and TensorFlow models
- Move a single model between Jax/PyTorch/TensorFlow frameworks at will
- Seamlessly pick the right framework for training, evaluation, production
Experimental support for Flax with a few models right now, expected to grow in the coming months.
The support for Jax is still experimental (with a few models right now), expect to see it grow in the coming months!
`All the model checkpoints <https://huggingface.co/models>`__ are seamlessly integrated from the huggingface.co `model
hub <https://huggingface.co>`__ where they are uploaded directly by `users <https://huggingface.co/users>`__ and
@@ -74,8 +74,8 @@ The documentation is organized in five parts:
- **MODELS** for the classes and functions related to each model implemented in the library.
- **INTERNAL HELPERS** for the classes and functions we use internally.
The library currently contains PyTorch, Tensorflow and Flax implementations, pretrained model weights, usage scripts
and conversion utilities for the following models:
The library currently contains Jax, PyTorch and Tensorflow implementations, pretrained model weights, usage scripts and
conversion utilities for the following models:
..
This list is updated automatically from the README with `make fix-copies`. Do not update manually!
@@ -251,8 +251,8 @@ and conversion utilities for the following models:
.. _bigtable:
The table below represents the current support in the library for each of those models, whether they have a Python
tokenizer (called "slow"). A "fast" tokenizer backed by the 🤗 Tokenizers library, whether they have support in PyTorch,
TensorFlow and/or Flax.
tokenizer (called "slow"). A "fast" tokenizer backed by the 🤗 Tokenizers library, whether they have support in Jax (via
Flax), PyTorch, and/or TensorFlow.
..
This table is updated automatically from the auto modules with `make fix-copies`. Do not update manually!