Instructions to use Tzohar/PassLLM-Qwen3-4B-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Tzohar/PassLLM-Qwen3-4B-v1.0 with PEFT:
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- Notebooks
- Google Colab
- Kaggle
PassLLM-Qwen3-4B-v1.0 (LoRA Adapter)
PassLLM is a state-of-the-art framework for AI-based targeted password guessing. This repository contains the LoRA weights for the Qwen3-4B base model, specifically fine-tuned to predict passwords based on Personally Identifiable Information (PII).
Model Details
| Feature | Specification |
|---|---|
| Base Model | Qwen3-4B |
| Training Method | LoRA (Low-Rank Adaptation) |
| Primary Datasets | PostMillennial, 000webhost, and ClixSense |
| Framework | PyTorch / PEFT |
How to Use
To use these weights with the PassLLM engine, please follow the installation and usage instructions on the official GitHub repository: ๐ PassLLM GitHub Repository
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Qwen/Qwen3-4B-Instruct-2507