weak to strong

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Quick description about weak to strong:

Weak-to-Strong is an OpenAI research codebase that implements the concept of weak-to-strong generalization, as described in the accompanying paper. The project provides tools for training larger �strong� models using labels or guidance generated by smaller �weak� models. Its core functionality focuses on binary classification tasks, with support for fine-tuning pretrained language models and experimenting with different loss functions, including confidence-based auxiliary losses. The repository also includes a dedicated vision module for applying weak-to-strong training setups in computer vision, demonstrated with models such as AlexNet and DINO on ImageNet. Although the code is not fully production-tested, it reproduces qualitatively similar results to the experiments presented in the paper, especially when comparing large model size gaps.

Features:

• Implements weak-to-strong training setups for language models
• Supports binary classification tasks with pretrained models
• Provides auxiliary loss functions such as confidence loss
• Includes a vision module for applying the method to image models
• Scripts for sweeping across different model size comparisons
• Tools for fine-tuning and training models with weak model labels

Programming Language: Python.
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