Instructions to use SandyTheAdventurer/spam-classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use SandyTheAdventurer/spam-classify with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("SandyTheAdventurer/spam-classify") - Notebooks
- Google Colab
- Kaggle
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Download README.md from SandyTheAdventurer/spam-classify: direct link, hf CLI and curl.
- Browser
- Download file 314 Bytes
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https://huggingface.co/SandyTheAdventurer/spam-classify/resolve/main/README.md
- Command line
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hf download hf://SandyTheAdventurer/spam-classify/README.md
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curl -L -o README.md https://huggingface.co/SandyTheAdventurer/spam-classify/resolve/main/README.md
314 Bytes
metadata
license: mit
language:
- en
library_name: tf-keras
widget:
- text: you have won 50000 cash!
example_title: Spam Classifier
pipeline_tag: text-classification
Use this model by using: model=tf.keras.models.load_model('model.keras')
This model Uses LSTM to predict if the given text is spam or not.