Instructions to use zeromodels/efficientdet_d1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use zeromodels/efficientdet_d1 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/efficientdet_d1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfae0c6949138bf8eb41116128baa281c5f9608239611ecf9d24a5bb759b9a4b
- Size of remote file:
- 28.3 MB
- SHA256:
- 1181a0c862d5e7bb8363ffea1f89e1bc9d5c72b90a878605cc4d78230aafa45e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.