Text Classification
Transformers
ONNX
Safetensors
modernbert
decision-steering
prompt-injection
indirect-prompt-injection
ai-agent-security
guardrails
llm-security
ai-safety
decision-model
jev-like
model-agnostic
erase-and-check
claim-detection
security
multilingual
mmbert
cpu
patronus
Eval Results (legacy)
text-embeddings-inference
Instructions to use patronus-studio/decision-steering-gate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patronus-studio/decision-steering-gate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="patronus-studio/decision-steering-gate")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("patronus-studio/decision-steering-gate") model = AutoModelForSequenceClassification.from_pretrained("patronus-studio/decision-steering-gate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!