Instructions to use Al-Chan/Malicious_Prompt_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Al-Chan/Malicious_Prompt_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Al-Chan/Malicious_Prompt_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Al-Chan/Malicious_Prompt_Classifier") model = AutoModelForSequenceClassification.from_pretrained("Al-Chan/Malicious_Prompt_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a72da83b2a0c5dd3039d32d08b1338bbca280607fa9f8b606bab3f789ef4993d
- Size of remote file:
- 268 MB
- SHA256:
- 74a8f01f3f7b78723427fe79fb2c2ebc8aa084ade19febbb960f98c8539e328e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.