Text Classification
Keras
security
web-attack-detection
sql-injection
xss
command-injection
rasp
cnn
gru
Instructions to use YangYang-Research/web-attack-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use YangYang-Research/web-attack-detection 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://YangYang-Research/web-attack-detection") - Notebooks
- Google Colab
- Kaggle
Download model.h5 from YangYang-Research/web-attack-detection: direct link, hf CLI and curl.
- Browser
- Download file 30.6 MB
-
https://huggingface.co/YangYang-Research/web-attack-detection/resolve/main/model.h5
- Command line
-
hf download hf://YangYang-Research/web-attack-detection/model.h5
-
curl -L -o model.h5 https://huggingface.co/YangYang-Research/web-attack-detection/resolve/main/model.h5
30.6 MB
- Xet hash:
- d89af12558297feed85536e320c7dd0ddccb82b88c5766a12633a019c0893dfd
- Size of remote file:
- 30.6 MB
- SHA256:
- b2df921fc602839eb23d93c34ef6dcbaf850817ef5a8918b7adc14ba47bdbf83
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