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:
- b7d24bdbd5e0f91293242b040649bf1de1eee9a5f186eea19b84c394994c56de
- Size of remote file:
- 39.7 MB
- SHA256:
- 87e9ff76838b2db6187db28c49df87cc56478002db4ee12a7be4ee52b48983d1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.