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@@ -15,13 +15,12 @@ This model only contains the `GaudiConfig` file for running the [Swin Transforme
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  This enables to specify:
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  - `use_fused_adam`: whether to use Habana's custom AdamW implementation
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  - `use_fused_clip_norm`: whether to use Habana's fused gradient norm clipping operator
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- - `disable_autocast`: whether to disable autocast; this parameter takes precedence over --bf16 flag and is temporary as some scripts produce nan values.
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- In those cases this parameter is already present in huggingface topology Habana gaudi_config.json.
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  ## Usage
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  The model is instantiated the same way as in the Transformers library.
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- The only difference is that there are a few new training arguments specific to HPUs.
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  This model is supported only in mixed precision training with bf16 type.
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  [Here](https://github.com/huggingface/optimum-habana/blob/main/examples/image-classification/run_image_classification.py) is an image classification example script to fine-tune a model. You can run it with Swin with the following command:
 
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  This enables to specify:
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  - `use_fused_adam`: whether to use Habana's custom AdamW implementation
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  - `use_fused_clip_norm`: whether to use Habana's fused gradient norm clipping operator
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+ - `use_torch_autocast`: whether to use Torch Autocast for managing mixed precision
 
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  ## Usage
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  The model is instantiated the same way as in the Transformers library.
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+ The only difference is that there are a few new training arguments specific to HPUs.\
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  This model is supported only in mixed precision training with bf16 type.
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  [Here](https://github.com/huggingface/optimum-habana/blob/main/examples/image-classification/run_image_classification.py) is an image classification example script to fine-tune a model. You can run it with Swin with the following command: