Text Classification
Transformers
Safetensors
English
deberta-v2
prompt-injection
ai-safety
llm-security
jailbreak
deberta-v3
Eval Results (legacy)
text-embeddings-inference
Instructions to use dmilush/shieldlm-deberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmilush/shieldlm-deberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dmilush/shieldlm-deberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dmilush/shieldlm-deberta-base") model = AutoModelForSequenceClassification.from_pretrained("dmilush/shieldlm-deberta-base") - Notebooks
- Google Colab
- Kaggle
Ctrl+K