Instructions to use zeromodels/deberta_v3_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/deberta_v3_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/deberta_v3_base") - Keras
How to use zeromodels/deberta_v3_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/deberta_v3_base") - Notebooks
- Google Colab
- Kaggle
Download model.weights.h5 from zeromodels/deberta_v3_base: direct link, hf CLI and curl.
- Browser
- Download file 736 MB
-
https://huggingface.co/zeromodels/deberta_v3_base/resolve/main/model.weights.h5
- Command line
-
hf download hf://zeromodels/deberta_v3_base/model.weights.h5
-
curl -L -o model.weights.h5 https://huggingface.co/zeromodels/deberta_v3_base/resolve/main/model.weights.h5
736 MB
- Xet hash:
- b020b089452486c9d5480dcc2974df3d4611afa8ea15c13762e82a3e52d5ada9
- Size of remote file:
- 736 MB
- SHA256:
- fbf58fdd7d2daca908436162e4394fdf645d0185775aabb11d1a924921ca4342
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