<a rel="ugc" href="https://www.instagram.com/nastassja.kinski/">Nastassja Kinski </a>is a German actress and former model, known for roles in many films, including Tess (for which she won a Golden Globe) and Paris, Texas. With this embedding I've tried to capture <a rel="ugc" href="https://www.vogue.fr/fashion-culture/galerie/vintage-photos-nastassja-kinski">her looks in the 80s and 90s</a>.This is a 1000-step TI trained on a dataset of 18 images with my <a target="_blank" rel="ugc" href="https://imgur.com/a/dOJEZg2">usual settings</a>.Appreciate my work? My TIs are free, but you can always <a target="_blank" rel="ugc" href="https://www.buymeacoffee.com/jernaugurgeh">buy me a coffee</a>. :)Curious about my work process? I have summarized it <a target="_blank" rel="ugc" href="https://civarchive.com/models/56570/renata-valliulina?commentId=118383&amp;modal=commentThread">here</a>.<h2>How to create a good prompt using my TIs</h2>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 (nk1nsky:0.99), a woman, closeup zoomed in tight crop portrait, sitting at a (table on a seaside boardwalk cafe bar drinks cocktails:1.2) wearing a (button shirt:1.3) (drinks on table:1.3) (Lighting-Gold:1.2) foreground objects background details (masterpiece:1.2) (photorealistic:1.2) (bokeh:1.2) (best quality) (color grading) (detailed skin:1.3) (intricate) (8k) (HDR) (cinematic lighting:1.3) (sharp focus)"

Nastassja Kinski (80s/90s)

1000-step TI trained on a dataset of 18 images with my <a target="_blank" rel="ugc" href="https://imgur.com/a/dOJEZg2">usual settings</a>.

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