Training Stable Diffusion with Dreambooth
Stable Diffusion is trained on LAION-5B, a large-scale dataset comprising billions of general image-text pairs. However, it falls short of comprehending specific subjects and their generation in various contexts (often blurry, obscure, or nonsensical). To address this problem, fine-tuning the model for specific use cases becomes crucial. There are two important fine-tuning techniques for stable Diffusion: Textual inversion: This technique focuses on retraining the text embeddings of a model to inject a word as a subject. DreamBooth: Unlike textual inversion, […]
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