A commission of @Springbok707.
Kim Basinger is an American actress and model, winner of an Academy Award and known for roles in many notable films, including Batman and L.A. Confidential. My goal with this embedding was to somehow capture her looks of the late 70s and 80s.
This is a 1200-step TI trained on a dataset of 18 images (partly provided by @Springbok707) with my usual settings. However, this time I've tried a couple of new things: I left the initialization text completely blank (usually I leave a "*" symbol instead) and reduced the token count to just 2 (it's usually 5 for me). I think the results have been very good, so I may keep these settings in the future.
Appreciate my work? My TIs are free, but you can always buy me a coffee. :)
Curious about my work process? I have summarized it here.
How to create a good prompt using 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 (youngk1m:0.99), a woman, RAW, close portrait photo, long brown coat, long haircut, pale skin, slim body, (high detailed skin:1.2), 8k uhd, dslr, soft lighting, high quality, film grain, Fujifilm XT3 sharp focus, f 5.6"