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 body/body_shape_model.tflite from Chizzsam/shape-models-checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 13.4 kB
-
https://huggingface.co/Chizzsam/shape-models-checkpoints/resolve/main/body/body_shape_model.tflite
- Command line
-
hf download hf://Chizzsam/shape-models-checkpoints/body/body_shape_model.tflite
-
curl -L -o body_shape_model.tflite https://huggingface.co/Chizzsam/shape-models-checkpoints/resolve/main/body/body_shape_model.tflite
13.4 kB
- Xet hash:
- 7ea5b38a2402b2bb167b7857bc85c0f17ab3917d53c047deb46f804e00d1fb04
- Size of remote file:
- 13.4 kB
- SHA256:
- a2c3bf340a66a439c0df945f04200b8e73cbeb7b2f625b3597a7fadf766301e7
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