Instructions to use WhitzardAgent/TrustNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use WhitzardAgent/TrustNet with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/inspire/hdd/global_user/25015/models/Qwen2.5-3B-Instruct") model = PeftModel.from_pretrained(base_model, "WhitzardAgent/TrustNet") - Notebooks
- Google Colab
- Kaggle
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- The User Trust Score is a continuous value in [0,1], where values near 1 indicate strong trust in AI, values near 0 indicate pronounced skepticism, and intermediate values (e.g., 0.5) represent a neutral or ambiguous stance.
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## Links
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- [Paper](https://arxiv.org/abs/2504.13707) - arXiv:2504.13707
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- [GitHub Repository](https://github.com/Simoniracle/OpenDeception-Framework) - Source code and framework
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## Usage
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- The User Trust Score is a continuous value in [0,1], where values near 1 indicate strong trust in AI, values near 0 indicate pronounced skepticism, and intermediate values (e.g., 0.5) represent a neutral or ambiguous stance.
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## Links
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- [Paper](https://arxiv.org/abs/2504.13707) - arXiv:2504.13707[v3]
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- [GitHub Repository](https://github.com/Simoniracle/OpenDeception-Framework) - Source code and framework
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## Usage
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