<a target="_blank" rel="ugc" href="https://www.instagram.com/sharonstone/?theme=dark">Sharon Stone</a> is a world-renown actress born in 1958. She has starred in films such as Basic Instinct, Total Recall and Casino, among many others.This is a 135-step TI trained on a dataset of 15 images with<a target="_blank" rel="ugc" href="https://imgur.com/a/d348H3k"> these settings</a>. The embedding is based on Sharon's <a target="_blank" rel="ugc" href="https://www.hawtcelebs.com/wp-content/uploads/2020/05/sharon-stone-total-recall-promos-1990-15.jpg">80s and early 90s looks</a>. It's a bit finicky, so I suggest you take my example prompts and use them as a base to build your own in case you're not getting good results.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>.Do you have a specific idea for a TI in mind?<a target="_blank" rel="ugc" href="https://www.buymeacoffee.com/jernaugurgeh"> Visit my website </a>and let me know.<h2 id="heading-386">Building a good prompt with 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 beautiful (sh4r0nst0ne:0.99), a woman, perfect hair, posing seductively, (modern photo, __attire_mix__), (closeup portrait), jewelry, 24mm, (analog, cinematic, film grain:1.3), (outside of Berghain Panorama Bar, nighttime, gritty), ((detailed eyes)), (epicPhoto), (color picture:1.1)".Please also note that I'm using the <a target="_blank" rel="ugc" href="https://civarchive.com/models/58390?modelVersionId=62833">"add detail" LoRA</a> for my example pics. I recommend setting it around 0.5 for best results. CLIP Skip should always be set at 1 when generating pics with this TI.

Sharon Stone

This is step 135 of a TI trained on a dataset of 15 images with<a target="_blank" rel="ugc" href="https://imgur.com/a/d348H3k"> these settings</a>.

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