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👇 Link in the first reply! [PRIME set]
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Generating a 1024x1024 image with StableDiffusion 3 in KerasHub, using float16 inference.
The `generate` method is compiled, and compilation happens on the first call. The next time you call the model again you will reuse the same compiled function and it will be super fast.
Finding 4: Keras 3 delivers solid speedups over Keras 2 -- even when compiling Keras 2 to XLA.
Keras 3 consistently outperformed Keras 2 across all benchmarked models. SegmentAnything inference saw a 380% boost! StableDiffusion training throughput rose by over 150%, BERT training throughput rose by over 100%.
Simply upgrading from Keras 2 to Keras 3 (even while staying on TF) will make your models run faster.
New tutorial on use Textual Inversion to teach StableDiffusion about a new visual concept (such as a specific character) to generate more images featuring the same concept.