Kelly Brook (Kelly Ann Parsons) is a rather stunning human being. Born in 1979, this actress and model has what may be the brightest, most heart-warming smile ever to grace the planet (subjective opinion, definitely). Scientists at Texas University have apparently determined her to have the perfect body shape (objective opinion, ostensibly); can't say I have many quibbles with that conclusion.This 16-vector embedding was trained using the ADAMW scheduler with a constant learning rate (LR 0.00075, 350-step warmup); I configured a 12-image batch size with 25 steps per epoch which ran for 111 epochs (2775 steps). The training data consisted of 60 body photos (1x repeat; attention masked) and 80 cropped face closeups (3x repeat; attention masked), meaning each epoch ran through 300 images. The training dataset included a ton of pinup photos (from early-mid 2010s), so the outputs may trend risqué; I'd strongly recommend taking that into account with your negative prompts if you want to prevent NSFW generations. Training software utilized is the awesome OneTrainer (found here: <a target="_blank" rel="ugc" href="https://github.com/Nerogar/OneTrainer">https://github.com/Nerogar/OneTrainer</a>).Sample images were generated utilizing Highres fix. and Adetailer (face); no other embeddings or LoRa were used. Generation prompts are accurate - seeds may differ a bit from mine as I'm using a TRT/ONNX conversion of the base models to speed processing.

Kelly Brook Ti

This 16-vector embedding was trained using ADAMW with a constant scheduler (LR 0.00075, 350-step warmup); I configured a 12-image batch size with 25 steps per epoch which ran for 111 epochs (2775 steps). The training data consisted of 60 body photos (1x repeat; attention masked) and 80 cropped face closeups (3x repeat; attention masked), meaning each epoch ran through 300 images. The training dataset included a ton of pinup photos, so the outputs may trend risqué; I'd strongly recommend taking that into account with your negative prompts if you want to prevent NSFW generations. Training software utilized is the awesome OneTrainer (found here: <a target="_blank" rel="ugc" href="https://github.com/Nerogar/OneTrainer">https://github.com/Nerogar/OneTrainer</a>).

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