Instructions to use dokutoshi/owlvit-base-patch32_FT_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dokutoshi/owlvit-base-patch32_FT_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="dokutoshi/owlvit-base-patch32_FT_cppe5")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("dokutoshi/owlvit-base-patch32_FT_cppe5") model = AutoModelForZeroShotObjectDetection.from_pretrained("dokutoshi/owlvit-base-patch32_FT_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d468eb83fce80f71f64367119bae0bfd8060ce2b4acfc1ab9dcac0d0f4cd6c4
- Size of remote file:
- 4.92 kB
- SHA256:
- 3adcaa877fe28ce645daa8b323691afe54335b88dc68730aa5cd446d4dc27004
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.