Image Classification
Keras
LiteRT
TF-Keras
skin-disease
medical
efficientnet
dermatology
computer-vision
healthcare
Instructions to use avirajatfunstop/skin-condition-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use avirajatfunstop/skin-condition-classifier with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://avirajatfunstop/skin-condition-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 437774a398808b8c16a7feaf73cde73488207d352dacf2e66de26fe2d235294c
- Size of remote file:
- 2.62 MB
- SHA256:
- 1890b448f00b4e421286f24d827e126d4ae680e26e8baefa4ce498bb9a660ba8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.