Instructions to use Chizzsam/shape-models-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Chizzsam/shape-models-checkpoints with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://Chizzsam/shape-models-checkpoints") - Notebooks
- Google Colab
- Kaggle
Download face/face_state.json from Chizzsam/shape-models-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 120 Bytes
-
https://huggingface.co/Chizzsam/shape-models-checkpoints/resolve/main/face/face_state.json
- Command line
-
hf download hf://Chizzsam/shape-models-checkpoints/face/face_state.json
-
curl -L -o face_state.json https://huggingface.co/Chizzsam/shape-models-checkpoints/resolve/main/face/face_state.json
120 Bytes
| { | |
| "phase": "done", | |
| "base_epochs_done": 30, | |
| "finetune_epochs_done": 10, | |
| "cumulative_hours": 0.08784033146169451 | |
| } |