<a target="_blank" rel="ugc" href="https://www.instagram.com/itsandreabotez/?hl=en">Andrea Botez</a> is a Canadian chess player and streamer, the younger sister of <a rel="ugc" href="https://civarchive.com/models/12306/alexandra-botez-chess-player">Alexandra Botez</a>.Update: Retrained from scratch. I'm having trouble deciding between steps 1200 and 1000. The former seems more consistent, but the latter has produced some great results, so I will probably upload it as version 3.0 later.Version 3.1 is a 1200-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 beautiful (4ndr34b0t3z:0.99), a woman as a movie star, hair upsweep updo, sweater off-shoulders, trousers, at a movie premiere gala, dark moody ambience (masterpiece:1.2) (photorealistic:1.2) (bokeh) (best quality) (detailed skin:1.2) (intricate details) (nighttime) (8k) (HDR) (cinematic lighting) (sharp focus), (looking at the camera:1.1), (closeup portrait:1.1)"

Andrea Botez

As with her sister, I've applied my new training method to my dataset of Andrea. The new TI has been trained for 6550 steps and seems less saturated and probably more accurate than the previous version, so I'm uploading it in case you wanna try it. Have fun!By the way, regarding prompt-building, I suggest you start the prompt with "a photo of", "a picture of", etc., and then you add "4ndreabotez". It seems to be much more precise that way. I've seen results that didn't have much to do with the subject when I started the prompt directly with "4ndreabotez". This is probably a consequence of how I train my models and the prompt template and filewords I use, but it seems unavoidable.

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