Token Classification
Transformers
Safetensors
English
modernbert
security
jailbreak-detection
prompt-injection
tool-calling
llm-safety
mcp
Eval Results (legacy)
Instructions to use vllm-sr/toolcall-verifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vllm-sr/toolcall-verifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vllm-sr/toolcall-verifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("vllm-sr/toolcall-verifier") model = AutoModelForTokenClassification.from_pretrained("vllm-sr/toolcall-verifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 248 Bytes
f9c8f39 | 1 2 3 4 5 6 7 8 | {
"accuracy": 0.9287719722676717,
"unauthorized_precision": 0.950093511979563,
"unauthorized_recall": 0.9204538309851105,
"unauthorized_f1": 0.9350388443092216,
"unauthorized_avg_f1": 0.9350388443092216,
"macro_f1": 0.9281028494375871
} |