Instructions to use google/owlv2-large-patch14-ensemble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/owlv2-large-patch14-ensemble with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="google/owlv2-large-patch14-ensemble")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("google/owlv2-large-patch14-ensemble") model = AutoModelForZeroShotObjectDetection.from_pretrained("google/owlv2-large-patch14-ensemble", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from google/owlv2-large-patch14-ensemble: direct link, hf CLI and curl.
- Browser
- Download file 1.75 GB
-
https://huggingface.co/google/owlv2-large-patch14-ensemble/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://google/owlv2-large-patch14-ensemble/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/google/owlv2-large-patch14-ensemble/resolve/main/pytorch_model.bin
1.75 GB
- Xet hash:
- 12216c78486dc76b59e5e46445cbe49539429d82d31359e35cb42546cc63b4a2
- Size of remote file:
- 1.75 GB
- SHA256:
- 2934e1f32c68b49f62e9b7a415c22080a8bf197c50c6f4408f4a60e21e0be252
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