Instructions to use zeromodels/dinov2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/dinov2-base 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/dinov2-base") - Keras
How to use zeromodels/dinov2-base 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/dinov2-base") - Notebooks
- Google Colab
- Kaggle
File size: 521 Bytes
6a16797 ce1e302 | 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": "zeromodels",
"zeromodels_version": "1.2.1",
"preprocessor_module": "zeromodels.models.dino_v2",
"preprocessor_class": "DinoV2ImageProcessor",
"variant": "dinov2-base",
"resize_size": 256,
"crop_size": 224,
"mean": [
0.48500001430511475,
0.4560000002384186,
0.4059999883174896
],
"std": [
0.2290000021457672,
0.2240000069141388,
0.22499999403953552
],
"do_center_crop": true,
"do_normalize": true,
"do_resize": true,
"data_format": "channels_last"
} |