<a target="_blank" rel="ugc" href="https://www.instagram.com/missbotez/?hl=en">Alexandra Botez</a> is a Canadian chess player and streamer, and the older sister of <a target="_blank" rel="ugc" href="https://civarchive.com/models/12764/andrea-botez-chess-player">Andrea Botez</a>.Update: Retrained from scratch, applying my <a target="_blank" rel="ugc" href="https://imgur.com/a/d348H3k">current settings</a>. This version is step 135 of a TI trained on a dataset of 15 images.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 (m1ssb0tez:0.99), a woman with perfect hair, wearing Golden Yellow (cassock:1.1), (cosmic background:1.1), (closeup), modelshoot style, (extremely detailed CG unity 8k wallpaper), professional majestic photography, (Leica M6 Camera), 24mm, exposure blend, hdr, faded, extremely intricate, High (Detail:1.1), Sharp focus, dramatic, soft cinematic light, (looking at viewer), (detailed pupils), 4k textures, elegant, ((((cinematic look)))), soothing tones, insane details, hyperdetailed, low contrast".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.

Alexandra Botez

The previous model was quite overtrained, as @epinikion mentioned in his review, so I decided to take a look a it again, review the filewords (I've reached the conclusion that the correct use of commas is fundamental if you mark the "Shuffle tags by ',' when creating prompts" option) and retrain. I interrupted the process at 750 steps, tested the embedding and I gotta say I'm quite satisfied with what I see. It seems both less saturated and probably more accurate than the previous model. Please let me know your impressions!

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