Zero-Shot Object Detection
ZeroModels
Keras
PyTorch
JAX
TensorFlow
owlvit
open-vocabulary
object-detection
Instructions to use zeromodels/owlvit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/owlvit-base-patch32 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/owlvit-base-patch32") - Keras
How to use zeromodels/owlvit-base-patch32 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/owlvit-base-patch32") - Notebooks
- Google Colab
- Kaggle
Upload kf_config.json with huggingface_hub
Browse files- kf_config.json +23 -0
kf_config.json
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{
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"library_name": "kerasformers",
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"kerasformers_version": "1.1.3",
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"model_module": "kerasformers.models.owlvit",
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"model_class": "OwlViTDetect",
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"variant": "owlvit-base-patch32",
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"weights": "model.weights.h5",
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"model_type": "owlvit",
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"vision_image_size": 768,
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"vision_patch_size": 32,
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"vision_hidden_dim": 768,
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"vision_intermediate_size": 3072,
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"vision_num_layers": 12,
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"vision_num_heads": 12,
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"text_hidden_dim": 512,
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"text_intermediate_size": 2048,
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"text_num_heads": 8,
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"projection_dim": 512,
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"text_num_layers": 12,
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"text_max_position_embeddings": 16,
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"text_vocab_size": 49408,
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"image_size": null
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}
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