Instructions to use sharktide/QuakeNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use sharktide/QuakeNet with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://sharktide/QuakeNet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 434bf2cd178be1e04634b3293ff7fffc3325b0e35c9cb6478f90a50aa8a3b38a
- Size of remote file:
- 64 kB
- SHA256:
- 20e65f21a5b8175b942f1e9ff472420ea4ec22a90d6f55e34a78d3a9003e4d7e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.