#foundation models
autodistill
Autodistill enhances AI model development by converting unlabeled images into inferable models suitable for edge deployment without manual input. Utilizing comprehensive foundation models for automatic dataset labeling, it specializes in vision tasks such as object detection and instance segmentation. Autodistill provides a modular interface for seamless model integration and deployment, making it a practical tool for developers focused on efficiency and performance.
AGIEval
AGIEval is a benchmark crafted to evaluate the problem-solving and cognitive capabilities of foundation models using tasks from exams like the Chinese Gaokao and American SAT. With the latest update to version 1.1, AGIEval offers MCQ and cloze tasks and provides performance evaluations across models such as GPT-3.5-Turbo and GPT-4o. This benchmark enables objective assessments and ensures researchers can identify model strengths and weaknesses.
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