Instructions to use shivalikasingh/shiftViT-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use shivalikasingh/shiftViT-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://shivalikasingh/shiftViT-Model") - Notebooks
- Google Colab
- Kaggle
| library_name: keras | |
| tags: | |
| - ShiftVit | |
| - Image Classification | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| | Hyperparameters | Value | | |
| | :-- | :-- | | |
| | name | AdamW | | |
| | learning_rate.class_name | WarmUpCosine | | |
| | learning_rate.config.lr_start | 1e-05 | | |
| | learning_rate.config.lr_max | 0.001 | | |
| | learning_rate.config.total_steps | 15625 | | |
| | learning_rate.config.warmup_steps | 2343 | | |
| | decay | 0.0 | | |
| | beta_1 | 0.8999999761581421 | | |
| | beta_2 | 0.9990000128746033 | | |
| | epsilon | 1e-07 | | |
| | amsgrad | False | | |
| | weight_decay | 9.999999747378752e-05 | | |
| | exclude_from_weight_decay | None | | |
| | training_precision | float32 | | |
| ## Model Plot | |
| <details> | |
| <summary>View Model Plot</summary> | |
|  | |
| </details> |