Text Classification
Transformers
ONNX
Safetensors
English
deberta-v2
prompt-injection
injection
security
llm-security
Generated from Trainer
text-embeddings-inference
Instructions to use protectai/deberta-v3-base-prompt-injection-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use protectai/deberta-v3-base-prompt-injection-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="protectai/deberta-v3-base-prompt-injection-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("protectai/deberta-v3-base-prompt-injection-v2") model = AutoModelForSequenceClassification.from_pretrained("protectai/deberta-v3-base-prompt-injection-v2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
using model with rust-bert
#5
by telelvis - opened
Hello !
I am trying to use the model onnx variant with Rust, I wonder if you have experience with rust-bert crate and can advise anything. In a nutshell I get significantly different results than with python-transformers.
Please have a look https://github.com/guillaume-be/rust-bert/issues/471