Instructions to use Juna190825/github_jeffprosise_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Juna190825/github_jeffprosise_model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Juna190825/github_jeffprosise_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2cb413920ce581d3778ba6980b451f80bd188b04ec804a3c72227373e76d3a6e
- Size of remote file:
- 435 MB
- SHA256:
- 622015a1fb86a700b091c279aff771b7bdfb642b6922743d431aa5fa6378346c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.