Instructions to use suvmkr/classification_between_6_types with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use suvmkr/classification_between_6_types 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://suvmkr/classification_between_6_types") - Notebooks
- Google Colab
- Kaggle
Classification Between 6 Types
This is a Convolutional Neural Network (CNN) model trained to classify images into six categories.
Model Details
- Framework: TensorFlow/Keras
- Model Format:
.keras - Input Image Size:
150x150 - Classes: [buildings,forest,glacier,mountain,sea,street]
Load the Model
from tensorflow.keras.models import load_model
model = load_model("https://huggingface.co/suvmkr/classification_between_6_types/resolve/main/yes.keras")
- Downloads last month
- -
# !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://suvmkr/classification_between_6_types")