Hypernetwork models are small neural networks for modifying styles. — Updated on 2024-03-03 11:50:38 — Group: Public
Hypernetwork cannot function alone. It needs to work with a checkpoint model to generate images. — Updated on 2024-03-03 11:52:17 — Group: Public
LoRA models are most similar to hypernetworks. They are both small and only modify the cross-attention module. The difference lies in how they modify it. A LoRA model modifies the cross-attention by changing its weight. Hypernetwork does it by inserting additional networks. Users generally find LoRA models produce better results. Their file sizes are similar, typically below 200MB, and way smaller than checkpoint models. — Updated on 2024-03-03 11:52:58 — Group: Public
Embeddings are the result of a fine-tuning method called textual inversion. Like hypernetwork, textual inversion does not change the model. It simply defines new keywords to achieve certain styles — Updated on 2024-03-03 11:54:01 — Group: Public