| |
| |
| import os |
| os.environ["KERAS_BACKEND"] = "tensorflow" |
| |
| from tensorflow.keras.models import load_model |
| from sentence_transformers import SentenceTransformer |
| from huggingface_hub import hf_hub_download |
|
|
|
|
| def load_modeler(): |
| local_model_path = hf_hub_download( |
| repo_id="noobpk/web-attack-detection", |
| filename="model.h5" |
| ) |
| return load_model(local_model_path) |
| |
| model = load_modeler() |
|
|
| def load_encoder(): |
| model_name_or_path = os.environ.get("model_name_or_path", "sentence-transformers/all-MiniLM-L6-v2") |
| return SentenceTransformer(model_name_or_path) |
|
|
| encoder = load_encoder() |
|
|
| if __name__ == "__main__": |
| payload = input("Enter payload: ") |
| print("Processing...") |
|
|
| embeddings = encoder.encode(payload).reshape((1, 384)) |
| prediction = model.predict(embeddings) |
| accuracy = float(prediction[0][0] * 100) |
| print(f"Accuracy: {accuracy}") |
|
|
