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
how can i finetune owlvit?
#13 opened 11 months ago
by
verityyyyyyy
Adding ONNX file of this model
#11 opened about 2 years ago
by
optowo
OWL-VIT Finetuning code for custom dataset in Hugging Face
#10 opened over 2 years ago
by
solomonpm
How can I ensemble multiple text/image queries?
#7 opened almost 3 years ago
by
flavourabbit
HuggingFace integration reference image mode works significantly worse than original repository
5
#6 opened about 3 years ago
by
maxtes