Instructions to use hayulalab/Circuit-Aware-SAIF-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use hayulalab/Circuit-Aware-SAIF-7B with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Circuit-Aware-SAIF-7B hayulalab/Circuit-Aware-SAIF-7B
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Circuit-Aware SAIF-7B
ุณูููู โ "sword" in Arabic
LoRA adapter for Qwen2.5-7B, trained with Circuit-Aware methodology using J-lens (Global Workspace Theory) to reduce hallucinations in security vulnerability analysis.
Training Details
- Base Model: Qwen/Qwen2.5-7B
- Rank: 32
- Iterations: 1000
- Batch Size: 4
- Learning Rate: 1e-5
- Val Loss: 2.051
- Train Loss: 0.043
Dataset
430 Arabic-English security samples across 9 domains: WebApp, Network, Reverse Engineering, Exploitation, Kernel, Browser, Vulnerability Discovery, Bug Bounty, Exploiter
Circuit-Aware Methodology
This adapter was trained using J-lens circuit mapping, which analyzes model activation patterns across 28 transformer layers to identify and strengthen factual reasoning circuits while suppressing hallucination-prone pathways.
Hardware compatibility
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Model tree for hayulalab/Circuit-Aware-SAIF-7B
Base model
Qwen/Qwen2.5-7B