Instructions to use google/owlv2-base-patch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/owlv2-base-patch16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="google/owlv2-base-patch16")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("google/owlv2-base-patch16") model = AutoModelForZeroShotObjectDetection.from_pretrained("google/owlv2-base-patch16") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "Owlv2ForObjectDetection" | |
| ], | |
| "initializer_factor": 1.0, | |
| "logit_scale_init_value": 2.6592, | |
| "model_type": "owlv2", | |
| "projection_dim": 512, | |
| "text_config": { | |
| "model_type": "owlv2_text_model" | |
| }, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.35.0.dev0", | |
| "vision_config": { | |
| "image_size": 960, | |
| "model_type": "owlv2_vision_model", | |
| "patch_size": 16 | |
| } | |
| } | |