Natalie Lee, better known as <a target="_blank" rel="ugc" href="https://www.instagram.com/natalee.007">NataLee</a>, Instagram model and influencer.Update: I wasn't 100% happy with version 2.0 and I've retrained the TI from scratch with my <a target="_blank" rel="ugc" href="https://imgur.com/a/d348H3k">current settings</a>. The current version (3.1) is step 130 of the new embedding. I'll probably add step 135 later at some point as version 3.0, since I think it's also pretty accurate and I had some trouble deciding between the two.Curious about my work process? I have summarized it<a target="_blank" rel="ugc" href="https://ko-fi.com/Post/My-TI-Training-Process-E1E1V8KLC"> here</a>.Appreciate my work? My TIs are free, but you can always <a target="_blank" rel="ugc" href="https://ko-fi.com/jernaugurgeh22606">buy me a coffee</a>. :)<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 (natal33:0.99), a woman as a movie star, modelshoot style, (extremely detailed CG unity 8k wallpaper), photo of the most beautiful artwork in the world, professional majestic oil painting by Ed Blinkey, Atey Ghailan, Studio Ghibli, by Jeremy Mann, Greg Manchess, Antonio Moro, trending on ArtStation, trending on CGSociety, Intricate, High Detail, Sharp focus, dramatic, photorealistic painting art by midjourney and greg rutkowski, (white turtleneck top:1.2), ((movie premiere)), (long skirt), ((standing near a movie theater)), ((paparazzi in the background)), (looking at viewer:1.2), (detailed pupils:1.3), ((closeup portrait:1.1))"

NataLee (JG)

My very first embedding. It had a tendency to depict NataLee as a brunette, but other than that I think it was a pretty good TI. I probably got kind of lucky, as I didn't really know most of what I was doing at the time. xDAccording to the automatically generated log, these were the settings I used: "num_of_dataset_images": 23, "num_vectors_per_token": 5, "embedding_name": "n4t4lee", "learn_rate": "0.004", "batch_size": 3, "training_width": 512, "training_height": 512, "steps": 1500,Unfortunately I don't know what gradient I used. I suspect it was gradient 1, but I'm not 100% sure about it.

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