140-step TI trained on a dataset of 15 images with these settings.










A commission of @Springbok707.
Emma Watson is a British actress who needs no introduction. For this embedding, the original idea was to capture her 2010 looks, with that famous pixie haircut.
Update: I've now updated the TI to look more like nowadays Emma. Version 3.0 is step 140 of a TI trained on a dataset of 15 images with these settings. It solves mainly some issues with her hair and her eyes present in v2.0.
Curious about my work process? I have summarized it here.
If you want to help me keep creating TIs, please consider buying me a coffee.
Also, I appreciate 5-star ratings if you really like my TIs!
You're obviously free to experiment, but bear in mind that my TIs are trained with a more or less fixed phrasing, that normally starts with:
"photo of EMBEDDING_NAME, a woman"
So I recommend always starting your prompt like that and then building the rest of the prompt from there. For instance, "photo of (emm4w4ts0n:0.99), a woman as a movie star, modelshoot style, (extremely detailed CG unity 8k wallpaper), photo of the most beautiful artwork in the world, professional majestic oil painting by Ed Blinkey, Atey Ghailan, Studio Ghibli, by Jeremy Mann, Greg Manchess, Antonio Moro, trending on ArtStation, trending on CGSociety, Intricate, High Detail, Sharp focus, dramatic, photorealistic painting art by midjourney and greg rutkowski, (white turtleneck top:1.2), ((movie premiere)), (long skirt), ((standing near a movie theater)), ((paparazzi in the background)), (looking at viewer:1.2), (detailed pupils:1.3), ((closeup portrait:1.1))"
140-step TI trained on a dataset of 15 images with these settings.
1. 재게시된 모델의 권리는 원 제작자에게 있습니다.
2. 모델 원작자가 모델을 인증받으려면 공식 채널을 통해 SeaArt.AI 직원에게 문의하세요. 저희는 모든 창작자의 권리를 보호하기 위해 노력합니다. 인증하러 이동
