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
|
Download README.md from SandyTheAdventurer/spam-classify: direct link, hf CLI and curl.
- Browser
- Download file 314 Bytes
-
https://huggingface.co/SandyTheAdventurer/spam-classify/resolve/main/README.md
- Command line
-
hf download hf://SandyTheAdventurer/spam-classify/README.md
-
curl -L -o README.md https://huggingface.co/SandyTheAdventurer/spam-classify/resolve/main/README.md
314 Bytes
| 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. |