Instructions to use zeromodels/levit-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/levit-384 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/levit-384") - Keras
How to use zeromodels/levit-384 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/levit-384") - Notebooks
- Google Colab
- Kaggle
Download model.weights.h5 from zeromodels/levit-384: direct link, hf CLI and curl.
- Browser
- Download file 158 MB
-
https://huggingface.co/zeromodels/levit-384/resolve/main/model.weights.h5
- Command line
-
hf download hf://zeromodels/levit-384/model.weights.h5
-
curl -L -o model.weights.h5 https://huggingface.co/zeromodels/levit-384/resolve/main/model.weights.h5
158 MB
- Xet hash:
- e756d79c2f0080a52c67c53af1cadfd55c4604dabde6bfdeb3577e212b215370
- Size of remote file:
- 158 MB
- SHA256:
- 266c0b1cb6a8d76c64904a88dab14cd300b30ce2b3ae9f45fdae251da178942f
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