Instructions to use buio/vq-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use buio/vq-vae with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://buio/vq-vae") - Notebooks
- Google Colab
- Kaggle
| library_name: keras | |
| tags: | |
| - computer-vision | |
| - generative | |
| - variational-autoencoder | |
| - vq-vae | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training Metrics | |
| Model history needed | |
| ## Model Plot | |
| <details> | |
| <summary>View Model Plot</summary> | |
|  | |
| </details> |