, a woman, modelshoot style, (extremely detailed CG unity 8k wallpaper), photo of the most beautifu.jpeg)
, a woman as a movie star, hair upsweep updo, sweater off-shoulders, trousers, at a movie.jpeg)
, a woman as a movie star, (looking at the camera), hair upsweep updo, sweater off-should.jpeg)
, a woman as a sexy housewife, (sexy denim overalls with cleavage_1.1), (woods cabin in the backgro.jpeg)
, a woman as a jedi master, modelshoot style, (extremely detailed CG unity 8k wallpaper), large bre.jpeg)
, a woman as a movie star, hair upsweep updo, sweater off-shoulders, trousers, at a movie.jpeg)
Type | |
Stats | 1,006 |
Reviews | (106) |
Published | Jun 23, 2023 |
Base Model | |
Training | Steps: 600 Epochs: 200 |
Trigger Words | m1ngnawen-600 |
Hash | AutoV2 68D3810488 |
A commission of @Zorglub.
Ming-Na Wen is an American actress of Chinese descent, known for her roles in many movies and different TV shows, including The Mandalorian and The Book of Boba Fett.
This TI trained really fast, and I ended up selecting step 600 as the best one out of the handful I tested. As usual, it was trained on a dataset of 18 images and with my standard settings.
Appreciate my work? My TIs are free, but you can always buy me a coffee. :)
Curious about my work process? I have summarized it here.
How to create a good prompt using my TIs
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 (m1ngnawen-600:0.99), a woman, RAW, close portrait photo, bodysuit with zipper, cleavage, fishnet stockings, pale skin, slim body, (high detailed skin:1.2), 8k uhd, dslr, soft lighting, high quality, film grain, Fujifilm XT3 sharp focus, f 5.6"