Instructions to use ryanlinjui/darkchess-robot-eye-AlexLeNet-9L with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ryanlinjui/darkchess-robot-eye-AlexLeNet-9L with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://ryanlinjui/darkchess-robot-eye-AlexLeNet-9L") - Notebooks
- Google Colab
- Kaggle
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## Model description
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This model serves as the **Eye of Darkchess Robot**, used to recognize the real-world Darkchess board.
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### Architecture
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Based on [AlexNet](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf) and [LeNet](https://yann.lecun.com/exdb/publis/pdf/lecun-98.pdf), with modifications to theirs architecture and parameters.
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## Model description
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This model serves as the **Eye of Darkchess Robot**, used to recognize the real-world Darkchess board.
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> For more imformation, please visit: https://github.com/ryanlinjui/darkchess-robot
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### Architecture
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Based on [AlexNet](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf) and [LeNet](https://yann.lecun.com/exdb/publis/pdf/lecun-98.pdf), with modifications to theirs architecture and parameters.
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