Instructions to use zeromodels/bert_base_uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/bert_base_uncased 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/bert_base_uncased") - Keras
How to use zeromodels/bert_base_uncased 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/bert_base_uncased") - Notebooks
- Google Colab
- Kaggle
Download model.weights.h5 from zeromodels/bert_base_uncased: direct link, hf CLI and curl.
- Browser
- Download file 535 MB
-
https://huggingface.co/zeromodels/bert_base_uncased/resolve/main/model.weights.h5
- Command line
-
hf download hf://zeromodels/bert_base_uncased/model.weights.h5
-
curl -L -o model.weights.h5 https://huggingface.co/zeromodels/bert_base_uncased/resolve/main/model.weights.h5
535 MB
- Xet hash:
- c35235b2a899a3acac285b16c31292aeb541329170e048b4bb49f0ebb3b03d72
- Size of remote file:
- 535 MB
- SHA256:
- 9cb43eb4ec873e51f645644aaf5cd623ab60b54ce56ee80e0e9a9fdb69eff402
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