Instructions to use zeromodels/efficientdet_d0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/efficientdet_d0 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/efficientdet_d0") - Keras
How to use zeromodels/efficientdet_d0 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/efficientdet_d0") - Notebooks
- Google Colab
- Kaggle
Download model.weights.h5 from zeromodels/efficientdet_d0: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/zeromodels/efficientdet_d0/resolve/main/model.weights.h5
- Command line
-
hf download hf://zeromodels/efficientdet_d0/model.weights.h5
-
curl -L -o model.weights.h5 https://huggingface.co/zeromodels/efficientdet_d0/resolve/main/model.weights.h5
16.8 MB
- Xet hash:
- d5dd536ec8416e3f91fee01a76f969f19f648a28096c4a8b79eb1f16a4e58291
- Size of remote file:
- 16.8 MB
- SHA256:
- 6aadfaa1721bbf380c4584e51602599e69e449e394b57f3c421daf908017884b
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