Instructions to use BeatThis/BeatThisModels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use BeatThis/BeatThisModels with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://BeatThis/BeatThisModels") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9101f0da3bd8fd41ec5e25c5fbb4e9c9ce94bbfc0f63631946478eee11fbb483
- Size of remote file:
- 39.7 MB
- SHA256:
- ead676fbd1a2a92bf7863fae8376c64cd1c3f3e9e3aeaec75724f7832d6ae6c8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.