Zero-Shot Object Detection
ZeroModels
Keras
PyTorch
JAX
TensorFlow
owlv2
open-vocabulary
object-detection
Instructions to use zeromodels/owlv2-base-patch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/owlv2-base-patch16 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") - Keras
How to use zeromodels/owlv2-base-patch16 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") - Notebooks
- Google Colab
- Kaggle
Upgrade kf_config.json to v2 (nested config + weight_dtype)
Browse files- kf_config.json +1 -1
kf_config.json
CHANGED
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@@ -6,7 +6,7 @@
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"variant": "owlv2-base-patch16",
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"weights": "model.weights.h5",
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"schema_version": 2,
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"
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"model_type": "owlv2",
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"text_config": {
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"hidden_dim": 512,
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"variant": "owlv2-base-patch16",
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"weights": "model.weights.h5",
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"schema_version": 2,
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"weight_dtype": "float32",
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"model_type": "owlv2",
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"text_config": {
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"hidden_dim": 512,
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