Instructions to use labhamlet/wavjepa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use labhamlet/wavjepa-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="labhamlet/wavjepa-base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("labhamlet/wavjepa-base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "auto_map": { | |
| "AutoFeatureExtractor": "feature_extraction_wavjepa.WavJEPAFeatureExtractor" | |
| }, | |
| "feature_extractor_type": "WavJEPAFeatureExtractor", | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| } | |