Instructions to use kerasformers/owlv2-large-patch14-ensemble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use kerasformers/owlv2-large-patch14-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-large-patch14-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-large-patch14-ensemble") - Notebooks
- Google Colab
- Kaggle
File size: 626 Bytes
cc0e3d2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"library_name": "kerasformers",
"kerasformers_version": "1.1.3",
"preprocessor_module": "kerasformers.models.owlv2",
"preprocessor_class": "Owlv2ImageProcessor",
"variant": "owlv2-large-patch14-ensemble",
"size": {
"height": 1008,
"width": 1008
},
"resample": "bicubic",
"do_rescale": true,
"rescale_factor": 0.00392156862745098,
"do_pad": true,
"do_normalize": true,
"image_mean": [
0.48145466,
0.4578275,
0.40821073
],
"image_std": [
0.26862954,
0.26130258,
0.27577711
],
"return_tensor": true,
"data_format": "channels_last"
} |