Instructions to use wangyh6/BlazeFace with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wangyh6/BlazeFace with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="wangyh6/BlazeFace", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wangyh6/BlazeFace", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c88beb326358f75d2dc9c8591064cc84df198fca67832dbf6d2764d799b8239
- Size of remote file:
- 412 kB
- SHA256:
- 4b1b873fa868df292abd44b5fc1a08849d9503e99ad3cae2582710000ac22354
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