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Title fix in PyTorch colab #2241

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Apr 19, 2024
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Title fix in PyTorch colab #2241

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c9b6150
title fix in colab
GleasonK Apr 19, 2024
f57b71e
Link fixing
GleasonK Apr 19, 2024
1ce3b76
link fix
GleasonK Apr 19, 2024
45869a5
remove extra link
GleasonK Apr 19, 2024
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10 changes: 7 additions & 3 deletions docs/tutorials/jax-export.ipynb
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Expand Up @@ -19,13 +19,17 @@
"source": [
"# Tutorial: Exporting StableHLO from JAX\n",
"\n",
"[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/stablehlo/blob/main/docs/tutorials/jax-export.ipynb) [![Open in Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://github.com/openxla/stablehlo/blob/main/docs/tutorials/jax-export.ipynb)\n",
"[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)][jax-tutorial-colab]\n",
"[![Open in Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)][jax-tutorial-kaggle]\n",
"\n",
"## Tutorial Setup\n",
"\n",
"### Install required dependencies\n",
"\n",
"We'll be using `jax` and `jaxlib` (JAX's XLA package), along with `flax` and `transformers` for some models to export."
"We'll be using `jax` and `jaxlib` (JAX's XLA package), along with `flax` and `transformers` for some models to export.\n",
"\n",
"[jax-tutorial-colab]: https://colab.research.google.com/github/openxla/stablehlo/blob/main/docs/examples/jax-export.ipynb\n",
"[jax-tutorial-kaggle]: https://kaggle.com/kernels/welcome?src=https://github.com/openxla/stablehlo/blob/main/docs/examples/jax-export.ipynb"
],
"metadata": {
"id": "_TuAgGNKt5HO"
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"\n",
"It is common to want to export a StableHLO model to SavedModel for interop with existing compilation pipelines, existing TF tooling, or serving via [TF Serving](https://github.com/tensorflow/serving).\n",
"\n",
"It is easy to pack StableHLO into a SavedModel, and load that SavedModel in the future. For this section we'll be using our dynamic model from the previous section."
"JAX makes it easy to pack StableHLO into a SavedModel, and load that SavedModel in the future. For this section we'll be using our dynamic model from the previous section."
],
"metadata": {
"id": "xFU5M6Xm1U8_"
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10 changes: 7 additions & 3 deletions docs/tutorials/pytorch-export.ipynb
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{
"cell_type": "markdown",
"source": [
"# # Tutorial: Exporting StableHLO from PyTorch\n",
"# Tutorial: Exporting StableHLO from PyTorch\n",
"\n",
"[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/stablehlo/blob/main/docs/tutorials/pytorch-export.ipynb) [![Open in Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://github.com/openxla/stablehlo/blob/main/docs/tutorials/pytorch-export.ipynb)\n",
"[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)][pytorch-tutorial-colab]\n",
"[![Open in Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)][pytorch-tutorial-kaggle]\n",
"\n",
"_Intro to the [`torch_xla.stablehlo`](https://github.com/pytorch/xla/blob/main/docs/stablehlo.md) module._\n",
"\n",
"## Tutorial Setup\n",
"\n",
"### Install required dependencies\n",
"\n",
"We'll be using `torch` and `torchvision` to get a `resnet18` model, and `torch_xla` to export to StableHLO."
"We'll be using `torch` and `torchvision` to get a `resnet18` model, and `torch_xla` to export to StableHLO.\n",
"\n",
"[pytorch-tutorial-colab]: https://colab.research.google.com/github/openxla/stablehlo/blob/main/docs/tutorials/pytorch-export.ipynb\n",
"[pytorch-tutorial-kaggle]: https://kaggle.com/kernels/welcome?src=https://github.com/openxla/stablehlo/blob/main/docs/tutorials/pytorch-export.ipynb"
],
"metadata": {
"id": "42_6VTj7l_xS"
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