[examples/Flax] move the examples table up (#12341)
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@@ -19,6 +19,17 @@ This folder contains actively maintained examples of 🤗 Transformers using the
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*NOTE*: Currently, there is no "Trainer" abstraction for JAX/Flax -- all examples contain an explicit training loop.
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The following table lists all of our examples on how to use 🤗 Transformers with the JAX/Flax backend:
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- with information about the model and dataset used,
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- whether or not they leverage the [🤗 Datasets](https://github.com/huggingface/datasets) library,
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- links to **Colab notebooks** to walk through the scripts and run them easily.
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| Task | Example model | Example dataset | 🤗 Datasets | Colab
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|---|---|---|:---:|:---:|
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| [**`causal-language-modeling`**](https://github.com/huggingface/transformers/tree/master/examples/flax/language-modeling) | GPT2 | OSCAR | ✅ | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/causal_language_modeling_flax.ipynb)
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| [**`masked-language-modeling`**](https://github.com/huggingface/transformers/tree/master/examples/flax/language-modeling) | RoBERTa | OSCAR | ✅ | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/masked_language_modeling_flax.ipynb)
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| [**`text-classification`**](https://github.com/huggingface/transformers/tree/master/examples/flax/text-classification) | BERT | GLUE | ✅ | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/text_classification_flax.ipynb)
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## Intro: JAX and Flax
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[JAX](https://github.com/google/jax) is a numerical computation library that exposes a NumPy-like API with tracing capabilities. With JAX's `jit`, you can
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@@ -48,16 +59,3 @@ For a complete overview of models that are supported in JAX/Flax, please have a
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Over 3000 pretrained checkpoints are supported in JAX/Flax as of May 2021.
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Click [here](https://huggingface.co/models?filter=jax) to see the full list on the 🤗 hub.
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## Examples
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The following table lists all of our examples on how to use 🤗 Transformers with the JAX/Flax backend:
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- with information about the model and dataset used,
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- whether or not they leverage the [🤗 Datasets](https://github.com/huggingface/datasets) library,
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- links to **Colab notebooks** to walk through the scripts and run them easily.
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| Task | Example model | Example dataset | 🤗 Datasets | Colab
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|---|---|---|:---:|:---:|
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| [**`causal-language-modeling`**](https://github.com/huggingface/transformers/tree/master/examples/flax/language-modeling) | GPT2 | OSCAR | ✅ | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/causal_language_modeling_flax.ipynb)
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| [**`masked-language-modeling`**](https://github.com/huggingface/transformers/tree/master/examples/flax/language-modeling) | RoBERTa | OSCAR | ✅ | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/masked_language_modeling_flax.ipynb)
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| [**`text-classification`**](https://github.com/huggingface/transformers/tree/master/examples/flax/text-classification) | BERT | GLUE | ✅ | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/text_classification_flax.ipynb)
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