Instructions to use itshemantkmr/2D_Shape_Image_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use itshemantkmr/2D_Shape_Image_Classification 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://itshemantkmr/2D_Shape_Image_Classification") - Notebooks
- Google Colab
- Kaggle
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Download README.md from itshemantkmr/2D_Shape_Image_Classification: direct link, hf CLI and curl.
- Browser
- Download file 186 Bytes
-
https://huggingface.co/itshemantkmr/2D_Shape_Image_Classification/resolve/main/README.md
- Command line
-
hf download hf://itshemantkmr/2D_Shape_Image_Classification/README.md
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curl -L -o README.md https://huggingface.co/itshemantkmr/2D_Shape_Image_Classification/resolve/main/README.md
186 Bytes
metadata
license: apache-2.0
language:
- en
metrics:
- accuracy
base_model: google/mobilenet_v2_1.0_224
pipeline_tag: image-classification
datasets:
- itshemantkmr/2D_Shape_Image_Datasets