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") - Notebooks
- Google Colab
- Kaggle
Add hidden_act for Candle compatibility
Browse files- config.json +3 -2
config.json
CHANGED
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@@ -51,5 +51,6 @@
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"sparse_pred_ignore_index": -100,
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"sparse_prediction": false,
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"transformers_version": "4.57.3",
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"vocab_size": 50368
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| 51 |
"sparse_pred_ignore_index": -100,
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"sparse_prediction": false,
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"transformers_version": "4.57.3",
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"vocab_size": 50368,
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"hidden_act": "gelu"
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}
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