Instructions to use yangwang825/ecapa-aam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yangwang825/ecapa-aam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="yangwang825/ecapa-aam", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yangwang825/ecapa-aam", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d43ebbec546f5ad5fa4ba8dc58addff49cbcdeba60b06f7bdef12bc93ebc6b2
- Size of remote file:
- 24.9 MB
- SHA256:
- ae57119fa449643f00cdb1c107a568769efaf78237b45d6f72f99f2386f206c7
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