Zero-Shot Object Detection
ZeroModels
Keras
PyTorch
JAX
TensorFlow
owlv2
open-vocabulary
object-detection
Instructions to use zeromodels/owlv2-base-patch16-ensemble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/owlv2-base-patch16-ensemble with ZeroModels:
# pip install -U zeromodels # ZeroModels is pure Keras 3, so pick a backend: "jax", "torch" or "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" from zeromodels import AutoZModel # AutoZModel reads the repo's model_type and loads the matching class. # For a task head use the matching loader, e.g. AutoZMImageClassify / AutoZMDetect / # AutoZMSemanticSegment / AutoZMTextGenerate (see zeromodels.auto). model = AutoZModel.from_weights("zeromodels/owlv2-base-patch16-ensemble") - Keras
How to use zeromodels/owlv2-base-patch16-ensemble with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://zeromodels/owlv2-base-patch16-ensemble") - Notebooks
- Google Colab
- Kaggle
Download model.weights.h5 from zeromodels/owlv2-base-patch16-ensemble: direct link, hf CLI and curl.
- Browser
- Download file 619 MB
-
https://huggingface.co/zeromodels/owlv2-base-patch16-ensemble/resolve/main/model.weights.h5
- Command line
-
hf download hf://zeromodels/owlv2-base-patch16-ensemble/model.weights.h5
-
curl -L -o model.weights.h5 https://huggingface.co/zeromodels/owlv2-base-patch16-ensemble/resolve/main/model.weights.h5
619 MB
- Xet hash:
- 9ad5c2c2f9b049d5a7c5bc5b502fd690bd1bca9c1e730ef650723fab5f3bdc1e
- Size of remote file:
- 619 MB
- SHA256:
- 66c278ae3038010b120d47153554bdffa45d2bace865d71b9663fdab2baa25f1
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