Instructions to use google/owlv2-base-patch16-ensemble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/owlv2-base-patch16-ensemble 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-ensemble")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("google/owlv2-base-patch16-ensemble") model = AutoModelForZeroShotObjectDetection.from_pretrained("google/owlv2-base-patch16-ensemble") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
Browse filesThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to `pytorch_model.bin` but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e1e130b9e404cf91a75ad45644c1da9d7fa5284085eecc864266a6923efb99e7
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size 619918824
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