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
Alara Dirik commited on
Commit ·
acd4120
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Parent(s): 7d594ca
Update config.json
Browse files- config.json +1 -0
config.json
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"logit_scale_init_value": 2.6592,
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"model_type": "owlvit",
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"projection_dim": 512,
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"text_config": {
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"_name_or_path": "",
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"add_cross_attention": false,
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"logit_scale_init_value": 2.6592,
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"model_type": "owlvit",
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"projection_dim": 512,
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"return_dict": true,
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"text_config": {
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"_name_or_path": "",
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"add_cross_attention": false,
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