--- license: apache-2.0 --- [Optimum Habana](https://github.com/huggingface/optimum-habana) is the interface between the Hugging Face Transformers and Diffusers libraries and Habana's Gaudi processor (HPU). It provides a set of tools enabling easy and fast model loading, training and inference 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 and deploy Transformers and Diffusers models at [hf.co/hardware/habana](https://huggingface.co/hardware/habana). ## DistilBERT Base model HPU configuration This model only contains the `GaudiConfig` file for running the [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) model on Habana's Gaudi processors (HPU). **This model contains no model weights, only a GaudiConfig.** This enables to specify: - `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 - `use_torch_autocast`: whether to use Torch Autocast for managing mixed precision ## 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.\ It is strongly recommended to train this model doing bf16 mixed-precision training for optimal performance and accuracy. [Here](https://github.com/huggingface/optimum-habana/blob/main/examples/question-answering/run_qa.py) is a question-answering example script to fine-tune a model on SQuAD. You can run it with DistilBERT with the following command: ```bash PT_HPU_LAZY_MODE=0 PT_ENABLE_INT64_SUPPORT=1 python run_qa.py \ --model_name_or_path distilbert-base-uncased \ --gaudi_config_name Habana/distilbert-base-uncased \ --dataset_name squad \ --do_train \ --do_eval \ --per_device_train_batch_size 64 \ --per_device_eval_batch_size 8 \ --learning_rate 0.0005 \ --num_train_epochs 3 \ --max_seq_length 384 \ --output_dir /tmp/squad/ \ --use_habana \ --use_lazy_mode false \ --torch_compile \ --torch_compile_backend hpu_backend \ --throughput_warmup_steps 5\ --bf16 \ --save_strategy no \ --doc_stride 128 \ --overwrite_output_dir \ ``` Check the [documentation](https://huggingface.co/docs/optimum/habana/index) out for more advanced usage and examples.