Instructions to use MalyO2/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MalyO2/working with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="MalyO2/working")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("MalyO2/working") model = AutoModelForObjectDetection.from_pretrained("MalyO2/working") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f20aecd86d37025fefa0c730bca0a8b91ad2799837f73c194c2ce34803154673
- Size of remote file:
- 166 MB
- SHA256:
- d9e1627baa87deefbcc2357b681afc9c529f8e34b6453fba8e7ddc9fd37571fa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.