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Fix Broken Quickstart Links #2641

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2 changes: 1 addition & 1 deletion README.rst
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Expand Up @@ -137,7 +137,7 @@ Flax
for _ in range(10):
loss, (param_grads, other_grads) = fwd_bwd_fn(params, other_variables, inp)

For a more comprehensive tutorial, check out our `Quickstart Notebook <https://github.com/NVIDIA/TransformerEngine/blob/main/docs/examples/quickstart.ipynb>`_.
For a more comprehensive tutorial, check out our `JAX Integration Tutorial <https://github.com/NVIDIA/TransformerEngine/blob/main/docs/examples/te_jax_integration.ipynb>`_ or the `Getting Started Guide <https://github.com/NVIDIA/TransformerEngine/blob/main/docs/getting_started/index.rst>`_.
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@ptrendx ptrendx Feb 2, 2026

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Hi, could you switch the order of those to have the Getting Started page as the first one?

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@ptrendx ptrendx Feb 2, 2026

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Actually, maybe we should instead just point to the Getting Started HTML page here: https://docs.nvidia.com/deeplearning/transformer-engine/user-guide/getting_started.html

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@pggPL pggPL Feb 3, 2026

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For a more comprehensive tutorial, check out our `JAX Integration Tutorial <https://github.com/NVIDIA/TransformerEngine/blob/main/docs/examples/te_jax_integration.ipynb>`_ or the `Getting Started Guide <https://github.com/NVIDIA/TransformerEngine/blob/main/docs/getting_started/index.rst>`_.
For a more comprehensive tutorial, check out our `JAX Integration Tutorial <https://github.com/NVIDIA/TransformerEngine/blob/main/docs/examples/te_jax_integration.ipynb>`_ or the `Getting Started Guide <https://docs.nvidia.com/deeplearning/transformer-engine/user-guide/getting_started.html>`_.


.. overview-end-marker-do-not-remove

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4 changes: 2 additions & 2 deletions examples/README.md
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Expand Up @@ -23,8 +23,8 @@ Additionally, we offer [Jupyter notebook tutorials](https://github.com/NVIDIA/Tr
- **FP8 Weight Caching**: Avoiding redundant FP8 casting during multiple gradient accumulation steps to improve efficiency.
- [Introduction to FP8](https://github.com/NVIDIA/TransformerEngine/blob/main/docs/examples/fp8_primer.ipynb)
- Overview of FP8 datatypes (E4M3, E5M2), mixed precision training, delayed scaling strategies, and code examples for FP8 configuration and usage.
- [TE Quickstart](https://github.com/NVIDIA/TransformerEngine/blob/main/docs/examples/quickstart.ipynb)
- Introduction to TE, building a Transformer Layer using PyTorch, and instructions on integrating TE modules like Linear and LayerNorm.
- [TE JAX Integration Tutorial](https://github.com/NVIDIA/TransformerEngine/blob/main/docs/examples/te_jax_integration.ipynb)
- Introduction to integrating TE into an existing JAX model framework, building a Transformer Layer, and instructions on integrating TE modules like Linear and LayerNorm.
- [Basic MNIST Example](https://github.com/NVIDIA/TransformerEngine/tree/main/examples/pytorch/mnist)

# JAX
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