Instructions to use alterf/detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alterf/detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="alterf/detection")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("alterf/detection") model = AutoModel.from_pretrained("alterf/detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 211dd36a88149d8671cca2e050b2a7f10ca48e9319baa6769bf84da69d6f8e11
- Size of remote file:
- 115 MB
- SHA256:
- dcc5bdfb5d59a4a9f27bb3d2d7a2bc91541d13878fd406a8752230cb31867dd1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.