self-supervised learning

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Self-supervised learning is a machine learning approach where the model learns from unlabeled data by creating its own labels or tasks. This method helps in understanding data patterns and improving model performance without extensive human labeling.

What are the training data and techniques used for training DALL·E 2?

The training data for training DALL·E 2 consists of a diverse range of images and text descriptions to teach the model to generate images from textual prompts. The techniques used to train DALL·E 2 include self-supervised learning, transformer-based models, and large-scale datasets for improved performance.

March 18, 2024

self-supervised learning

What are the training data and techniques used for training DALL·E 2?

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