Text Classification
Transformers
Safetensors
English
modernbert
prompt-injection
jailbreak-detection
security
ModernBERT
ai-safety
inference-loop
text-embeddings-inference
Instructions to use theinferenceloop/vektor-guard-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theinferenceloop/vektor-guard-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="theinferenceloop/vektor-guard-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("theinferenceloop/vektor-guard-v1") model = AutoModelForSequenceClassification.from_pretrained("theinferenceloop/vektor-guard-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efd18d702adb9fbce070ee7caa3f577cdc37ce34e60d555ba234225f2b73818c
- Size of remote file:
- 1.58 GB
- SHA256:
- a9fdea268366907943d3c8d096d0a94339c55810d5579a7de3dd6387f3692700
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