Text Classification
Transformers
Safetensors
English
deberta-v2
prompt-injection
security
span-detection
guardrails
ai-safety
agents
llm-security
text-embeddings-inference
Instructions to use Unplug-AI/unplug-tiny-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Unplug-AI/unplug-tiny-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Unplug-AI/unplug-tiny-v1")# Load model directly from transformers import AutoTokenizer, DebertaV2ForDualHead tokenizer = AutoTokenizer.from_pretrained("Unplug-AI/unplug-tiny-v1") model = DebertaV2ForDualHead.from_pretrained("Unplug-AI/unplug-tiny-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75a61524fd1a826e086c9675521067a083f6083652f7091ce804aa2d4e8caa66
- Size of remote file:
- 283 MB
- SHA256:
- e8c89b0a347cf313f557c07dea1a117a698d2741970da0584e57330b355ee1d7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.