Token Classification
Transformers
Safetensors
English
modernbert
security
jailbreak-detection
prompt-injection
tool-calling
llm-safety
mcp
Eval Results (legacy)
Instructions to use rootfs/tool-call-verifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rootfs/tool-call-verifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rootfs/tool-call-verifier")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rootfs/tool-call-verifier") model = AutoModelForTokenClassification.from_pretrained("rootfs/tool-call-verifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5dead0eff9b8ffa49fc89fcacf76bc6987c2e0a3e1a9a695ada5de11c79ffeaf
- Size of remote file:
- 598 MB
- SHA256:
- 992a572e923cbb0b336b5ced300c43badc4e91934a32d5bd6dd66c8017e9d75b
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