| For example, create a default [Wav2Vec2FeatureExtractor] if you are using Wav2Vec2 for audio classification: | |
| from transformers import Wav2Vec2FeatureExtractor | |
| w2v2_extractor = Wav2Vec2FeatureExtractor() | |
| print(w2v2_extractor) | |
| Wav2Vec2FeatureExtractor { | |
| "do_normalize": true, | |
| "feature_extractor_type": "Wav2Vec2FeatureExtractor", | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": false, | |
| "sampling_rate": 16000 | |
| } | |
| If you aren't looking for any customization, just use the from_pretrained method to load a model's default feature extractor parameters. |