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
Upload face/face_shape_labels.json with huggingface_hub
Browse files- face/face_shape_labels.json +34 -0
face/face_shape_labels.json
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{
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"model_version": "3.1.0",
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"input": {
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"shape": [
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1,
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224,
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224,
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3
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],
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"dtype": "float32",
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"range": [
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0.0,
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255.0
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],
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"layout": "NHWC",
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"color_order": "RGB",
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"preprocessing": "none \u2014 normalization is baked into the model"
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},
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"output": {
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"shape": [
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1,
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5
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],
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"dtype": "float32",
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"type": "softmax"
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},
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"labels": [
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"Heart",
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"Oblong",
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"Oval",
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"Round",
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"Square"
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]
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}
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