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README.md
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[Optimum Habana](https://github.com/huggingface/optimum-habana) is the interface between the Transformers library and Habana's Gaudi processor (HPU). It provides a set of tools enabling easy and fast model loading and fine-tuning on single- and multi-HPU settings for different downstream tasks.
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Learn more about how to take advantage of the power of Habana HPUs to train Transformers models at [hf.co/Habana](https://huggingface.co/Habana).
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## RoBERTa Base model HPU configuration
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This model contains just the `GaudiConfig` file for running the [roberta-base](https://huggingface.co/roberta-base) model on Habana's Gaudi processors (HPU).
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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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## Usage
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The model is instantiated the same way as in the Transformers library.
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from optimum.habana import GaudiConfig, GaudiTrainer, GaudiTrainingArguments
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from transformers import RobertaModel, RobertaTokenizer
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tokenizer = RobertaTokenizer.from_pretrained("roberta-base")
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model = RobertaModel.from_pretrained("roberta-base")
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gaudi_config = GaudiConfig.from_pretrained("Habana/roberta-base")
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[Optimum Habana](https://github.com/huggingface/optimum-habana) is the interface between the Transformers library and Habana's Gaudi processor (HPU). It provides a set of tools enabling easy and fast model loading and fine-tuning on single- and multi-HPU settings for different downstream tasks.
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Learn more about how to take advantage of the power of Habana HPUs to train Transformers models at [hf.co/Habana](https://huggingface.co/Habana).
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## RoBERTa Base model HPU configuration
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This model contains just the `GaudiConfig` file for running the [roberta-base](https://huggingface.co/roberta-base) model on Habana's Gaudi processors (HPU).
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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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## Usage
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The model is instantiated the same way as in the Transformers library.
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from optimum.habana import GaudiConfig, GaudiTrainer, GaudiTrainingArguments
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from transformers import RobertaModel, RobertaTokenizer
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tokenizer = RobertaTokenizer.from_pretrained("roberta-base")
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model = RobertaModel.from_pretrained("roberta-base")
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gaudi_config = GaudiConfig.from_pretrained("Habana/roberta-base")
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