Instructions to use zeromodels/clip_vit_base_32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/clip_vit_base_32 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/clip_vit_base_32") - Keras
How to use zeromodels/clip_vit_base_32 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/clip_vit_base_32") - Notebooks
- Google Colab
- Kaggle
File size: 508 Bytes
51e8be5 cf862c4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"library_name": "zeromodels",
"zeromodels_version": "1.1.3",
"preprocessor_module": "zeromodels.models.clip",
"preprocessor_class": "CLIPImageProcessor",
"variant": "clip_vit_base_32",
"image_resolution": 224,
"mean": [
0.48145467042922974,
0.45782750844955444,
0.40821072459220886
],
"std": [
0.2686295509338379,
0.2613025903701782,
0.27577710151672363
],
"do_center_crop": true,
"do_normalize": true,
"do_resize": true,
"data_format": "channels_last"
} |