readme: ---
  license: apache-2.0
  ---
  
  [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.
  Learn more about how to take advantage of the power of Habana HPUs to train Transformers models at [hf.co/hardware/habana](https://huggingface.co/hardware/habana).
  
  ## GPT2 model HPU configuration
  
  This model only contains the `GaudiConfig` file for running the [GPT2](https://huggingface.co/gpt2) model on Habana's Gaudi processors (HPU).
  
  **This model contains no model weights, only a GaudiConfig.**
  
  This enables to specify:
  - `use_habana_mixed_precision`: whether to use Habana Mixed Precision (HMP)
      - `hmp_opt_level`: optimization level for HMP, see [here](https://docs.habana.ai/en/latest/PyTorch/PyTorch_Mixed_Precision/PT_Mixed_Precision.html#configuration-options) for a detailed explanation
      - `hmp_bf16_ops`: list of operators that should run in bf16
      - `hmp_fp32_ops`: list of operators that should run in fp32
      - `hmp_is_verbose`: verbosity
  - `use_fused_adam`: whether to use Habana's custom AdamW implementation
  - `use_fused_clip_norm`: whether to use Habana's fused gradient norm clipping operator
  
  ## Usage
  
  The model is instantiated the same way as in the Transformers library.
  The only difference is that there are a few new training arguments specific to HPUs.
  
  [Here](https://github.com/huggingface/optimum-habana/blob/main/examples/language-modeling/run_clm.py) is a causal language modeling example script to pre-train/fine-tune a model. You can run it with GPT2 with the following command:
  ```bash
  python run_clm.py \
      --model_name_or_path gpt2 \
      --dataset_name wikitext \
      --dataset_config_name wikitext-2-raw-v1 \
      --per_device_train_batch_size 4 \
      --per_device_eval_batch_size 4 \
      --do_train \
      --do_eval \
      --output_dir /tmp/test-clm \
      --gaudi_config_name Habana/gpt2 \
      --use_habana \
      --use_lazy_mode \
      --throughput_warmup_steps 2
  ```
  
  Check the [documentation](https://huggingface.co/docs/optimum/habana/index) out for more advanced usage and examples. 
  