Instructions to use google/owlvit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/owlvit-base-patch32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="google/owlvit-base-patch32")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("google/owlvit-base-patch32") model = AutoModelForZeroShotObjectDetection.from_pretrained("google/owlvit-base-patch32") - Notebooks
- Google Colab
- Kaggle
Update preprocessor_config.json (#4)
Browse files- Update preprocessor_config.json (762acffaca2b50d60dffeff460b91750f9fbc86f)
Co-authored-by: Alara Dirik <adirik@users.noreply.huggingface.co>
- preprocessor_config.json +1 -1
preprocessor_config.json
CHANGED
|
@@ -18,5 +18,5 @@
|
|
| 18 |
"processor_class": "OwlViTProcessor",
|
| 19 |
"resample": 3,
|
| 20 |
"rescale": true,
|
| 21 |
-
"size": 768
|
| 22 |
}
|
|
|
|
| 18 |
"processor_class": "OwlViTProcessor",
|
| 19 |
"resample": 3,
|
| 20 |
"rescale": true,
|
| 21 |
+
"size": [768, 768]
|
| 22 |
}
|