Image Classification
LiteRT
Keras
Burmese
tensorflow
burmese
myanmar
handwritten
digit-recognition
computer-vision
cnn
lightweight
edge-ai
Instructions to use Drew2456/MyanNet-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Drew2456/MyanNet-V1 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Drew2456/MyanNet-V1") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -284,7 +284,7 @@ If you use MyanNet V1 in your research, please cite:
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title = {MyanNet V1: A Lightweight CNN for Burmese Handwritten Digit Recognition},
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year = {2026},
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publisher = {Hugging Face},
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url = {https://huggingface.co/
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}
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```
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title = {MyanNet V1: A Lightweight CNN for Burmese Handwritten Digit Recognition},
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year = {2026},
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publisher = {Hugging Face},
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url = {https://huggingface.co/Drew2456/MyanNet-V1}
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}
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```
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