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The CLIP model is built on the concept of contrastive learning, which aims to learn aligned embeddings between text and images. Large-scale data collections are crucial for training and fine-tuning CLIP models. However, these collections can be cumbersome to manage, especially when dealing with massive amounts of data.

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