Text Classification
Transformers
Safetensors
English
distilbert
prompt-injection
security
cybersecurity
llm-security
ml-intern
text-embeddings-inference
Instructions to use av-codes/pi-detector-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use av-codes/pi-detector-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="av-codes/pi-detector-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("av-codes/pi-detector-distilbert") model = AutoModelForSequenceClassification.from_pretrained("av-codes/pi-detector-distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f313693aa84fa935f8cbf6ccbb8cc1c9901fb17d487dbbc5fd0bf25c78d88e2
- Size of remote file:
- 268 MB
- SHA256:
- f3ec844b481b829bfd89701701cf86ed6be606573f76e8ec3fa27b135dfc2387
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