Instructions to use facebook/w2v-bert-2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/w2v-bert-2.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/w2v-bert-2.0")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("facebook/w2v-bert-2.0") model = AutoModel.from_pretrained("facebook/w2v-bert-2.0") - Notebooks
- Google Colab
- Kaggle
| { | |
| "feature_extractor_type": "SeamlessM4TFeatureExtractor", | |
| "feature_size": 80, | |
| "num_mel_bins": 80, | |
| "padding_side": "right", | |
| "padding_value": 1, | |
| "processor_class": "Wav2Vec2BertProcessor", | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000, | |
| "stride": 2 | |
| } | |