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:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://YangYang-Research/web-attack-detection") - Notebooks
- Google Colab
- Kaggle
Communication regarding data sources and accuracy
#2
by redauzhang - opened
How are the current data sources and accuracy guaranteed? Have the injected samples generated by the large model been thoroughly tested? I had the large model directly generate injected black and white samples, and the accuracy was only 82%. Does this meet the model's expectations? For FN, there are a large number of Windows RFI samples with bypassed encoding.
redauzhang changed discussion status to closed