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[docs] add a mention of torchao and other backends in speed memory docs. #13499

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[docs] add a mention of torchao and other backends in speed memory docs. #13499

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2 changes: 2 additions & 0 deletions docs/source/en/optimization/speed-memory-optims.md
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Expand Up @@ -33,6 +33,8 @@ The table below provides a comparison of optimization strategy combinations and

This guide will show you how to compile and offload a quantized model with [bitsandbytes](../quantization/bitsandbytes#torchcompile). Make sure you are using [PyTorch nightly](https://pytorch.org/get-started/locally/) and the latest version of bitsandbytes.

While we use bitsandbytes in this example, other quantization backends such as [TorchAO](../quantization/torchao.md) also support these features.

```bash
pip install -U bitsandbytes
```
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