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@@ -91,7 +91,7 @@ The quantization methods supported are as follows:
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Some quantization methods are aliases (for example, `int8wo` is the commonly used shorthand for `int8_weight_only`). This allows using the quantization methods described in the torchao docs as-is, while also making it convenient to remember their shorthand notations.
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Refer to the official torchao documentation for a better understanding of the available quantization methods and the exhaustive list of configuration options available.
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Refer to the [official torchao documentation](https://docs.pytorch.org/ao/stable/index.html) for a better understanding of the available quantization methods and the exhaustive list of configuration options available.
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## Serializing and Deserializing quantized models
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@@ -155,5 +155,5 @@ transformer.load_state_dict(state_dict, strict=True, assign=True)
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## Resources
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- [TorchAO Quantization API](https://github.com/pytorch/ao/blob/main/torchao/quantization/README.md)
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- [TorchAO Quantization API](https://docs.pytorch.org/ao/stable/index.html)
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- [Diffusers-TorchAO examples](https://github.com/sayakpaul/diffusers-torchao)
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