Instructions to use Gwen01/ProctorVision-Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Gwen01/ProctorVision-Models 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://Gwen01/ProctorVision-Models") - Notebooks
- Google Colab
- Kaggle
Download best_threshold.npy from Gwen01/ProctorVision-Models: direct link, hf CLI and curl.
- Browser
- Download file 136 Bytes
-
https://huggingface.co/Gwen01/ProctorVision-Models/resolve/main/best_threshold.npy
- Command line
-
hf download hf://Gwen01/ProctorVision-Models/best_threshold.npy
-
curl -L -o best_threshold.npy https://huggingface.co/Gwen01/ProctorVision-Models/resolve/main/best_threshold.npy
136 Bytes
- Xet hash:
- 094cc5e417456e257353e8e4c0b68509f9c24aba5398d265da813fbbf4a9f3d6
- Size of remote file:
- 136 Bytes
- SHA256:
- a7cbe9d66fda4477730bfc94c0888c417b34caaf54ab9bbce4742f687f186ad6
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