LoRA model of alhaitham/アルハイゼン/艾尔海森 (Genshin Impact)
What Is This?
This is the LoRA model of waifu alhaitham/アルハイゼン/艾尔海森 (Genshin Impact).
How Is It Trained?
- This model is trained with kohya-ss/sd-scripts, and the test images are generated with a1111's webui and API sdk.
- The auto-training framework is maintained by DeepGHS Team.
The architecture of base model is is
SD1.5
. - Dataset used for training is the
stage3-p480-1200
in CyberHarem/alhaitham_genshin, which contains 1249 images. - Trigger word is
alhaitham_genshin
. - Pruned core tags for this waifu are
grey hair, short hair, multicolored hair, green eyes, ahoge, hair over one eye, swept bangs, sidelocks, hair between eyes, parted bangs
. You can add them to the prompt when some features of waifu (e.g. hair color) are not stable. - For more details in training, you can take a look at training configuration file.
- For more details in LoRA, you can download it, and read the metadata with a1111's webui.
How to Use It?
After downloading the safetensors files for the specified step, you need to use them like common LoRA.
- Recommended LoRA weight is 0.5-0.85.
- Recommended trigger word weight is 0.7-1.1.
For example, if you want to use the model from step 1162, you need to download 1162/alhaitham_genshin.safetensors
as LoRA. By using this model, you can generate images for the desired characters.
Which Step Should I Use?
We selected 5 good steps for you to choose. The best one is step 1162.
1220 images (1.23 GiB) were generated for auto-testing.
Here are the preview of the recommended steps:
Step | Epoch | CCIP | AI Corrupt | Bikini Plus | Score | Download | pattern_0_0 | pattern_0_1 | pattern_1 | pattern_2_0 | pattern_2_1 | pattern_3_0 | pattern_3_1 | pattern_4_0 | pattern_4_1 | pattern_5_0 | pattern_5_1 | pattern_6 | pattern_7_0 | pattern_7_1 | pattern_8 | pattern_9 | pattern_10_0 | pattern_10_1 | pattern_11 | pattern_12 | pattern_13 | pattern_14_0 | pattern_14_1 | pattern_15 | pattern_16 | pattern_17 | pattern_18 | portrait_0 | portrait_1 | portrait_2 | full_body_0 | full_body_1 | profile_0 | profile_1 | free_0 | free_1 | short | shirt_0 | shirt_1 | uniform_0 | uniform_1 | uniform_2 | suit_0 | suit_1 | jacket_0 | jacket_1 | swim_0 | swim_1 | swim_2 | sit | squat | kneel | jump | crossed_arms | angry | smile | cry | grin | n_stand_0 | n_stand_1 | n_stand_2 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1162 | 7 | 0.993 | 0.987 | 0.815 | 0.761 | Download | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3320 | 20 | 0.993 | 0.984 | 0.814 | 0.759 | Download | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1992 | 12 | 0.993 | 0.983 | 0.809 | 0.750 | Download | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1494 | 9 | 0.992 | 0.986 | 0.817 | 0.727 | Download | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
664 | 4 | 0.991 | 0.991 | 0.815 | 0.711 | Download |
Anything Else?
Because the automation of LoRA training always annoys some people. So for the following groups, it is not recommended to use this model and we express regret:
- Individuals who cannot tolerate any deviations from the original character design, even in the slightest detail.
- Individuals who are facing the application scenarios with high demands for accuracy in recreating character outfits.
- Individuals who cannot accept the potential randomness in AI-generated images based on the Stable Diffusion algorithm.
- Individuals who are not comfortable with the fully automated process of training character models using LoRA, or those who believe that training character models must be done purely through manual operations to avoid disrespecting the characters.
- Individuals who finds the generated image content offensive to their values.
All Steps
We uploaded the files in all steps. you can check the images, metrics and download them in the following links: