Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

removed paxml references from README #1271

Merged
merged 1 commit into from
Feb 6, 2025
Merged

removed paxml references from README #1271

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
53 changes: 2 additions & 51 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,15 +3,14 @@
[![License Apache 2.0](https://badgen.net/badge/license/apache2.0/blue)](https://github.com/NVIDIA/JAX-Toolbox/blob/main/LICENSE.md)
[![Build](https://badgen.net/badge/build/check-status/blue)](#build-pipeline-status)

JAX Toolbox provides a public CI, Docker images for popular JAX libraries, and optimized JAX examples to simplify and enhance your JAX development experience on NVIDIA GPUs. It supports JAX libraries such as [MaxText](https://github.com/google/maxtext), [Paxml](https://github.com/google/paxml), and [Pallas](https://jax.readthedocs.io/en/latest/pallas/quickstart.html).
JAX Toolbox provides a public CI, Docker images for popular JAX libraries, and optimized JAX examples to simplify and enhance your JAX development experience on NVIDIA GPUs. It supports JAX libraries such as [MaxText](https://github.com/google/maxtext) and [Pallas](https://jax.readthedocs.io/en/latest/pallas/quickstart.html).

## Frameworks and Supported Models
We support and test the following JAX frameworks and model architectures. More details about each model and available containers can be found in their respective READMEs.

| Framework | Models | Use cases | Container |
| :--- | :---: | :---: | :---: |
| [maxtext](./rosetta/rosetta/projects/maxtext)| GPT, LLaMA, Gemma, Mistral, Mixtral | pretraining | `ghcr.io/nvidia/jax:maxtext` |
| [paxml](./rosetta/rosetta/projects/pax) | GPT, LLaMA, MoE | pretraining, fine-tuning, LoRA | `ghcr.io/nvidia/jax:pax` |
| [t5x](./rosetta/rosetta/projects/t5x) | T5, ViT | pre-training, fine-tuning | `ghcr.io/nvidia/jax:t5x` |
| [t5x](./rosetta/rosetta/projects/imagen) | Imagen | pre-training | `ghcr.io/nvidia/t5x:imagen-2023-10-02.v3` |
| [big vision](./rosetta/rosetta/projects/paligemma) | PaliGemma | fine-tuning, evaluation | `ghcr.io/nvidia/jax:gemma` |
Expand Down Expand Up @@ -204,54 +203,6 @@ We support and test the following JAX frameworks and model architectures. More d
</a>
</td>
</tr>
<tr>
<td>
<a href="https://github.com/NVIDIA/JAX-Toolbox/blob/main/.github/container/Dockerfile.pax">
<img style="height:1em;" src="https://img.shields.io/static/v1?label=&color=gray&logo=docker&message=Upstream%20PAX%3D%7Bcore%2Cpaxml%2Cpraxis%7D">
</a>
</td>
<td>
<code>ghcr.io/nvidia/jax:upstream-pax</code>
</td>
<td>
<a href="https://gist.github.com/nvjax/913c2af68649fe568e9711c2dabb23ae/#file-final-upstream-pax-md">
<img style="height:1em;" src="https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2Fnvjax%2F913c2af68649fe568e9711c2dabb23ae%2Fraw%2Fbadge-pax-build-amd64.json&logo=docker&label=amd64">
</a>
<br>
<a href="https://gist.github.com/nvjax/913c2af68649fe568e9711c2dabb23ae/#file-final-upstream-pax-md">
<img style="height:1em;" src="https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2Fnvjax%2F913c2af68649fe568e9711c2dabb23ae%2Fraw%2Fbadge-pax-build-arm64.json&logo=docker&label=arm64">
</a>
</td>
<td>
<a href="https://gist.github.com/nvjax/913c2af68649fe568e9711c2dabb23ae#file-badge-upstream-pax-mgmn-test-json">
<img style="height:1em;" src="https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2Fnvjax%2F913c2af68649fe568e9711c2dabb23ae%2Fraw%2Fbadge-upstream-pax-mgmn-test.json&logo=nvidia&label=A100%20distributed">
</a>
</td>
</tr>
<tr>
<td>
<a href="https://github.com/NVIDIA/JAX-Toolbox/blob/main/rosetta/Dockerfile.pax">
<img style="height:1em;" src="https://img.shields.io/static/v1?label=&color=gray&logo=docker&message=Rosetta%20PAX%3D%7Bcore%2Cpaxml%2Cpraxis%7D">
</a>
</td>
<td>
<code>ghcr.io/nvidia/jax:pax</code>
</td>
<td>
<a href="https://gist.github.com/nvjax/913c2af68649fe568e9711c2dabb23ae/#file-final-pax-md">
<img style="height:1em;" src="https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2Fnvjax%2F913c2af68649fe568e9711c2dabb23ae%2Fraw%2Fbadge-rosetta-build-pax-amd64.json&logo=docker&label=amd64">
</a>
<br>
<a href="https://gist.github.com/nvjax/913c2af68649fe568e9711c2dabb23ae/#file-final-pax-md">
<img style="height:1em;" src="https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2Fnvjax%2F913c2af68649fe568e9711c2dabb23ae%2Fraw%2Fbadge-rosetta-build-pax-arm64.json&logo=docker&label=arm64">
</a>
</td>
<td>
<a href="https://gist.github.com/nvjax/913c2af68649fe568e9711c2dabb23ae#file-badge-rosetta-pax-mgmn-test-json">
<img style="height:1em;" src="https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2Fnvjax%2F913c2af68649fe568e9711c2dabb23ae%2Fraw%2Fbadge-rosetta-pax-mgmn-test.json&logo=nvidia&label=A100%20distributed">
</a>
</td>
</tr>
<tr>
<td>
<a href="https://github.com/NVIDIA/JAX-Toolbox/blob/main/.github/container/Dockerfile.maxtext">
Expand Down Expand Up @@ -317,7 +268,7 @@ The [JAX image](https://github.com/NVIDIA/JAX-Toolbox/pkgs/container/jax) is emb
| -------------------- | ----- | ----------- |
| `NCCL_NVLS_ENABLE` | `0` | Disables NVLink SHARP ([1](https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/env.html#nccl-nvls-enable)). Future releases will re-enable this feature. |

There are various other XLA flags users can set to improve performance. For a detailed explanation of these flags, please refer to the [GPU performance](./rosetta/docs/GPU_performance.md) doc. XLA flags can be tuned per workflow. For example, each script in [contrib/gpu/scripts_gpu](https://github.com/google/paxml/tree/main/paxml/contrib/gpu/scripts_gpu) sets its own [XLA flags](https://github.com/google/paxml/blob/93fbc8010dca95af59ab615c366d912136b7429c/paxml/contrib/gpu/scripts_gpu/benchmark_gpt_multinode.sh#L30-L33).
There are various other XLA flags users can set to improve performance. For a detailed explanation of these flags, please refer to the [GPU performance](./rosetta/docs/GPU_performance.md) doc. XLA flags can also be tuned per workload. For example, each script includes a directory [xla_flags](./rosetta/rosetta/projects/maxtext/xla_flags).

For a list of previously used XLA flags that are no longer needed, please also refer to the [GPU performance](./rosetta/docs/GPU_performance.md#previously-used-xla-flags) page.

Expand Down