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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 291 Bytes
7473c99 | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"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
}
|