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:
- c64df9abb2672b937b7115f3237ea6c690764efaeee3df2f08215764a552396b
- Size of remote file:
- 5.24 kB
- SHA256:
- f9c5c51611eed8d23035fec4b42ac33b6d1ec20f029f82b22506aa4229a06cf3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.