Text Classification
Transformers
Safetensors
English
modernbert
prompt-injection
jailbreak-detection
llm-security
guardrails
Eval Results (legacy)
text-embeddings-inference
Instructions to use theinferenceloop/vektor-guard-v3-interim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theinferenceloop/vektor-guard-v3-interim with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="theinferenceloop/vektor-guard-v3-interim")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("theinferenceloop/vektor-guard-v3-interim") model = AutoModelForSequenceClassification.from_pretrained("theinferenceloop/vektor-guard-v3-interim", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from theinferenceloop/vektor-guard-v3-interim: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/theinferenceloop/vektor-guard-v3-interim/resolve/main/tokenizer.json
- Command line
-
hf download hf://theinferenceloop/vektor-guard-v3-interim/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/theinferenceloop/vektor-guard-v3-interim/resolve/main/tokenizer.json
3.58 MB
File too large to display, you can check the raw version instead.