Text Classification
Transformers
ONNX
Safetensors
deberta-v2
llm-guard
security
text-embeddings-inference
Instructions to use TangoBeeAkto/deberta-prompt-injection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TangoBeeAkto/deberta-prompt-injection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TangoBeeAkto/deberta-prompt-injection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TangoBeeAkto/deberta-prompt-injection") model = AutoModelForSequenceClassification.from_pretrained("TangoBeeAkto/deberta-prompt-injection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from TangoBeeAkto/deberta-prompt-injection: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/TangoBeeAkto/deberta-prompt-injection/resolve/main/tokenizer.json
- Command line
-
hf download hf://TangoBeeAkto/deberta-prompt-injection/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/TangoBeeAkto/deberta-prompt-injection/resolve/main/tokenizer.json
8.66 MB
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