Instructions to use ilililili/furniture-ngpea_HWTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ilililili/furniture-ngpea_HWTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ilililili/furniture-ngpea_HWTest")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("ilililili/furniture-ngpea_HWTest") model = AutoModelForObjectDetection.from_pretrained("ilililili/furniture-ngpea_HWTest") - Notebooks
- Google Colab
- Kaggle
furniture-ngpea_HWTest / runs /Oct19_08-37-56_89cdec06e068 /events.out.tfevents.1760863614.89cdec06e068.1004.0
- Xet hash:
- 96283e959041712501c0aaae6c9702b587fc5e54ea036fd3e5de98dc83e024c4
- Size of remote file:
- 6.7 kB
- SHA256:
- 4e4617db8bc93e455c2763349c4fb39277f0c94313bd056390fca05bbbd66fae
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.