major-sdxl
major-sdxl
2 stars
README

For best outputs:

  • Sampler: DPM++ 2M Karras.

  • Steps: 30, cfg 5 ~ 7, CLIP skip 1.

  • VAE: none required.

  • Pos prompt: the model is set to realism, with realistic keywords can become even more realistic. Optional: add the LoRa "detailed_notrigger" with a weight of 1 at the end of your pos (found in most of my example runs).

  • Neg prompt: can be left blank / what you don't want to see.

Checkpoint Trained.

00000-2432402687.webp00000-2432402686%20(1).webpoutput-d943a070ab554108b4f9abf932abb712-00002-2432402690.webpoutput-ca74b02d3b934c49bdfff640c4e240b8-00000-582888724.webpoutput-d6dbb3c7ef5a47c6aad403cc29beea4a-00000-2432402688.webpoutput-3db6f477730e4a32a843e9ef95d6cd26-00002-582888726.webp00002-2432402688.webp00001-2432402688.webpoutput-780294591e814bdb93e7f3c2d79005db-00002-2432402690.webpoutput-070347930ae84b97bd3892e6d3996d51-00001-2432402687.webpoutput-2c4739ec16c8470fb384451ce4264f04-00001-582888725.webp00002-3697231594.webp00002-2432402689.webp00000-2432402688.webpoutput-9b7b6399e4ac40c4b68a9913dbc39522-00000-2432402688.webpoutput-8ee58ecda3d84bdcb132755ec3036277-00001-582888725.webpoutput-32caf8308bf44421961d93162b623a58-00000-272647671.webpoutput-7738281229df4664b0cb1db8bc343ee2-00000-272647671.webpoutput-47d3374232ac48798cab2890934886c2-00002-2432402690.webpoutput-e47f2ab38aa34ced9c8f01d886d13956-00001-2432402689.webpoutput-24473303bf014dc2997caf56b8b70381-00000-2432402688.webpoutput-4acb20291db94bf7bcccac125bd21e79-00001-582888725.webpoutput-4c9455ab7dd54313b5c6c736c452e3fd-00001-272647672.webp00000-2432402688%20(1).webp00001-2432402687.webp00001-2432402689.webp00000-2432402686%20(2).webp00000-2432402686.webpoutput-e8b13d690d8847dd80e93a3a494651ca-00000-2432402688.webpoutput-e59d6ec1e9c84392ac36c537dfb01394-00001-582888725.webpoutput-f443ef81a39249bb8ed9641faf7f1e7f-00001-2432402689.webpoutput-a7afbf7987eb4d5a8021fd9604bf6f02-00001-582888725.webpoutput-a21a1436388d441c978254679cbdcb5f-00002-2432402688.webpoutput-b21f86a7f40a442dac07fcf0f11bf391-00000-272647671.webpoutput-c2c3649fecf949e682cddae2d529044f-00002-582888726.webpoutput-8a5370e2cf8a4cd191aca6b7b2412497-00001-582888725.webpoutput-7d373641aa31454480f19da522b0cbd2-00001-2432402687.webpoutput-7c5b4e64f5534f7d98223c1260a5d2fa-00000-582888724.webpoutput-5a2be3ff3ccc44a392615035fafd085a-00002-272647673.webpoutput-05b9e125afd54f5587cfaae197dd9df1-00002-582888727.webp

For best outputs:

  • Sampler: DPM++ 2M Karras.

  • Steps: 30, cfg 5 ~ 7, CLIP skip 1.

  • VAE: none required.

  • Pos prompt: the model is set to realism, with realistic keywords can become even more realistic. Optional: add the LoRa "detailed_notrigger" with a weight of 1 at the end of your pos (found in most of my example runs).

  • Neg prompt: can be left blank / what you don't want to see.

Checkpoint Trained.

00000-2432402687.webp00000-2432402686%20(1).webpoutput-d943a070ab554108b4f9abf932abb712-00002-2432402690.webpoutput-ca74b02d3b934c49bdfff640c4e240b8-00000-582888724.webpoutput-d6dbb3c7ef5a47c6aad403cc29beea4a-00000-2432402688.webpoutput-3db6f477730e4a32a843e9ef95d6cd26-00002-582888726.webp00002-2432402688.webp00001-2432402688.webpoutput-780294591e814bdb93e7f3c2d79005db-00002-2432402690.webpoutput-070347930ae84b97bd3892e6d3996d51-00001-2432402687.webpoutput-2c4739ec16c8470fb384451ce4264f04-00001-582888725.webp00002-3697231594.webp00002-2432402689.webp00000-2432402688.webpoutput-9b7b6399e4ac40c4b68a9913dbc39522-00000-2432402688.webpoutput-8ee58ecda3d84bdcb132755ec3036277-00001-582888725.webpoutput-32caf8308bf44421961d93162b623a58-00000-272647671.webpoutput-7738281229df4664b0cb1db8bc343ee2-00000-272647671.webpoutput-47d3374232ac48798cab2890934886c2-00002-2432402690.webpoutput-e47f2ab38aa34ced9c8f01d886d13956-00001-2432402689.webpoutput-24473303bf014dc2997caf56b8b70381-00000-2432402688.webpoutput-4acb20291db94bf7bcccac125bd21e79-00001-582888725.webpoutput-4c9455ab7dd54313b5c6c736c452e3fd-00001-272647672.webp00000-2432402688%20(1).webp00001-2432402687.webp00001-2432402689.webp00000-2432402686%20(2).webp00000-2432402686.webpoutput-e8b13d690d8847dd80e93a3a494651ca-00000-2432402688.webpoutput-e59d6ec1e9c84392ac36c537dfb01394-00001-582888725.webpoutput-f443ef81a39249bb8ed9641faf7f1e7f-00001-2432402689.webpoutput-a7afbf7987eb4d5a8021fd9604bf6f02-00001-582888725.webpoutput-a21a1436388d441c978254679cbdcb5f-00002-2432402688.webpoutput-b21f86a7f40a442dac07fcf0f11bf391-00000-272647671.webpoutput-c2c3649fecf949e682cddae2d529044f-00002-582888726.webpoutput-8a5370e2cf8a4cd191aca6b7b2412497-00001-582888725.webpoutput-7d373641aa31454480f19da522b0cbd2-00001-2432402687.webpoutput-7c5b4e64f5534f7d98223c1260a5d2fa-00000-582888724.webpoutput-5a2be3ff3ccc44a392615035fafd085a-00002-272647673.webpoutput-05b9e125afd54f5587cfaae197dd9df1-00002-582888727.webp
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Updated on Jun 25, 2024
evevalentine2017/major-sdxl
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