Text Classification
Transformers
Safetensors
English
modernbert
security
jailbreak-detection
prompt-injection
llm-safety
Eval Results (legacy)
text-embeddings-inference
Instructions to use rootfs/function-call-sentinel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rootfs/function-call-sentinel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rootfs/function-call-sentinel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rootfs/function-call-sentinel") model = AutoModelForSequenceClassification.from_pretrained("rootfs/function-call-sentinel") - Notebooks
- Google Colab
- Kaggle
| { | |
| "classification_report": { | |
| "SAFE": { | |
| "precision": 0.9489615554573575, | |
| "recall": 0.97193935279475, | |
| "f1-score": 0.9603130240357741, | |
| "support": 4419.0 | |
| }, | |
| "INJECTION_RISK": { | |
| "precision": 0.9714614499424626, | |
| "recall": 0.9481132075471698, | |
| "f1-score": 0.959645333636467, | |
| "support": 4452.0 | |
| }, | |
| "accuracy": 0.9599819637019502, | |
| "macro avg": { | |
| "precision": 0.9602115026999101, | |
| "recall": 0.9600262801709598, | |
| "f1-score": 0.9599791788361205, | |
| "support": 8871.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.9602533523514717, | |
| "recall": 0.9599819637019502, | |
| "f1-score": 0.9599779369364938, | |
| "support": 8871.0 | |
| } | |
| }, | |
| "accuracy": 0.9599819637019502, | |
| "macro_f1": 0.9599791788361205, | |
| "weighted_f1": 0.9599779369364938, | |
| "injection_precision": 0.9714614499424626, | |
| "injection_recall": 0.9481132075471698, | |
| "injection_f1": 0.959645333636467, | |
| "roc_auc": 0.9928215719631005 | |
| } |