Zero-Shot Object Detection
KerasFormers
Keras
PyTorch
JAX
TensorFlow
owlv2
open-vocabulary
object-detection
Instructions to use kerasformers/owlv2-base-patch16-ensemble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/owlv2-base-patch16-ensemble with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use kerasformers/owlv2-base-patch16-ensemble with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://kerasformers/owlv2-base-patch16-ensemble") - Notebooks
- Google Colab
- Kaggle
File size: 667 Bytes
c96ce9e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"library_name": "kerasformers",
"kerasformers_version": "1.1.3",
"model_module": "kerasformers.models.owlv2",
"model_class": "Owlv2Detect",
"variant": "owlv2-base-patch16-ensemble",
"weights": "model.weights.h5",
"model_type": "owlv2",
"vision_image_size": 960,
"vision_patch_size": 16,
"vision_hidden_dim": 768,
"vision_intermediate_size": 3072,
"vision_num_layers": 12,
"vision_num_heads": 12,
"text_hidden_dim": 512,
"text_intermediate_size": 2048,
"text_num_heads": 8,
"projection_dim": 512,
"text_num_layers": 12,
"text_max_position_embeddings": 16,
"text_vocab_size": 49408,
"image_size": null
} |