Text Classification
Scikit-learn
Joblib
Keras
English
cybersecurity
http-attack-detection
intrusion-detection
web-security
tfidf
xgboost
lightgbm
Instructions to use cycloevan/http-attack-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use cycloevan/http-attack-classification with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("cycloevan/http-attack-classification", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Keras
How to use cycloevan/http-attack-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://cycloevan/http-attack-classification") - Notebooks
- Google Colab
- Kaggle
Download rf_basic.joblib from cycloevan/http-attack-classification: direct link, hf CLI and curl.
- Browser
- Download file 152 MB
-
https://huggingface.co/cycloevan/http-attack-classification/resolve/main/rf_basic.joblib
- Command line
-
hf download hf://cycloevan/http-attack-classification/rf_basic.joblib
-
curl -L -o rf_basic.joblib https://huggingface.co/cycloevan/http-attack-classification/resolve/main/rf_basic.joblib
152 MB
- Xet hash:
- 2c44907d149965e787d133581e0abc245effa9742cd90b3ca12b76c02a06a235
- Size of remote file:
- 152 MB
- SHA256:
- fad53ec475bbf7393970a379a5a6dc7561f5822bf50e64462bd2fe5c2625be7c
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