Update README.md

README.md

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 license: apache-2.0
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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.
+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).
+
+## Wav2Vec2 model HPU configuration
+
+This model only contains the `GaudiConfig` file for running the [Wav2Vec2](https://huggingface.co/facebook/wav2vec2-base) 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/audio-classification/run_audio_classification.py) is an audio classification example script to fine-tune a model. You can run it with Wav2Vec2 with the following command:
+```bash
+python run_audio_classification.py \
+    --model_name_or_path facebook/wav2vec2-base \
+    --dataset_name superb \
+    --dataset_config_name ks \
+    --output_dir /tmp/wav2vec2-base-ft-keyword-spotting \
+    --overwrite_output_dir \
+    --remove_unused_columns False \
+    --do_train \
+    --do_eval \
+    --learning_rate 3e-5 \
+    --max_length_seconds 1 \
+    --attention_mask False \
+    --warmup_ratio 0.1 \
+    --num_train_epochs 5 \
+    --per_device_train_batch_size 256 \
+    --per_device_eval_batch_size 256 \
+    --dataloader_num_workers 4 \
+    --seed 27 \
+    --use_habana \
+    --use_lazy_mode \
+    --gaudi_config_name Habana/wav2vec2 \
+    --throughput_warmup_steps 2
+```
+
+Check the [documentation](https://huggingface.co/docs/optimum/habana/index) out for more advanced usage and examples.