Text Classification
Keras
English
Azerbaijani
prompt-injection
security
llm-security
document-security
retvec
cnn
tensorflow
fastapi
Eval Results (legacy)
Instructions to use MegrurNiftiyev/MyGuard-Prompt-Injection-Detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use MegrurNiftiyev/MyGuard-Prompt-Injection-Detector with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://MegrurNiftiyev/MyGuard-Prompt-Injection-Detector") - Notebooks
- Google Colab
- Kaggle
Download conftest.py from MegrurNiftiyev/MyGuard-Prompt-Injection-Detector: direct link, hf CLI and curl.
- Browser
- Download file 298 Bytes
-
https://huggingface.co/MegrurNiftiyev/MyGuard-Prompt-Injection-Detector/resolve/main/conftest.py
- Command line
-
hf download hf://MegrurNiftiyev/MyGuard-Prompt-Injection-Detector/conftest.py
-
curl -L -o conftest.py https://huggingface.co/MegrurNiftiyev/MyGuard-Prompt-Injection-Detector/resolve/main/conftest.py
298 Bytes
| """ | |
| Root conftest — sets environment variables BEFORE any app module is imported. | |
| This avoids pydantic-settings ValidationError during collection. | |
| """ | |
| import os | |
| # Set required env vars before anything else imports app.core.config | |
| os.environ.setdefault("INTERNAL_SERVICE_TOKEN", "test-secret") | |