Instructions to use tecncr/osteosarcoma-detect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use tecncr/osteosarcoma-detect with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://tecncr/osteosarcoma-detect") - Notebooks
- Google Colab
- Kaggle
Nicolas Castillo commited on
initial upload
Browse files- EfficientNetB0_osteosarcoma.h5 +3 -0
- MobileNetV2_osteosarcoma.h5 +3 -0
- ResNet50_osteosarcoma.h5 +3 -0
- VGG16_osteosarcoma.h5 +3 -0
EfficientNetB0_osteosarcoma.h5
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size 20881968
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MobileNetV2_osteosarcoma.h5
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size 13523024
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ResNet50_osteosarcoma.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:fe946d0b093fcaffd6d77f21911e3afe39f75499305d89dbeb9a6c8a31f8c4b8
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size 107557776
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VGG16_osteosarcoma.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:d0bc08d4837e43ef7faa8da6acc104a04c12ca01941f302fb5dd73a2bcbc418c
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size 62133120
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