Instructions to use 360TechEnv/waste-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use 360TechEnv/waste-classifier with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://360TechEnv/waste-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d54f320d253dd9cf2cc8baa229563ede4270511d53736edb315971fa54592912
- Size of remote file:
- 4.14 MB
- SHA256:
- ff3320e6df42edd9e1e996ad47cf2fe8fcf1a9b42d87d1b0a11ca63b42868aaf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.