Instructions to use zeromodels/efficientdet_d6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/efficientdet_d6 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_d6") - Keras
How to use zeromodels/efficientdet_d6 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_d6") - Notebooks
- Google Colab
- Kaggle
Download model.weights.h5 from zeromodels/efficientdet_d6: direct link, hf CLI and curl.
- Browser
- Download file 212 MB
-
https://huggingface.co/zeromodels/efficientdet_d6/resolve/main/model.weights.h5
- Command line
-
hf download hf://zeromodels/efficientdet_d6/model.weights.h5
-
curl -L -o model.weights.h5 https://huggingface.co/zeromodels/efficientdet_d6/resolve/main/model.weights.h5
212 MB
- Xet hash:
- 22c9825e7797b4c9df4666a5f16b33f7b5ea0f2055a727dcc8ce083d2a5e8539
- Size of remote file:
- 212 MB
- SHA256:
- fa131996891803718629dd00af34aa6447ac344c6bdd5e6958cc8c070b287404
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.