Instructions to use fxmarty/owlvit-tiny-non-contiguous-weight with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fxmarty/owlvit-tiny-non-contiguous-weight with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="fxmarty/owlvit-tiny-non-contiguous-weight")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("fxmarty/owlvit-tiny-non-contiguous-weight") model = AutoModelForZeroShotObjectDetection.from_pretrained("fxmarty/owlvit-tiny-non-contiguous-weight", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ecc66140fe2c3e50070258553a7f7f506e0272c21af3aaf770aa1917d4046a46
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size 1558544
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