Text-to-Image
Diffusers
English
lora
template:diffusion-lora
noobai
noobaixl
illustrious
v-pred
noobai_eps
noobai_vpred
Instructions to use robb-0/Isometrix_NoobAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use robb-0/Isometrix_NoobAI with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Laxhar/noobai-XL-1.1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("robb-0/Isometrix_NoobAI") prompt = "isometric view, detailed anime mini +5boys, perfect anatomy, cook, uniform, cook hat, apron, cook uniform, clothed, cooking, baking, cleaning, detailed industrial kitchen decorations ,window, , from above, from isometric, 3d, absuredres, perfect quality, detailed background,, very aesthetic, absurdres, newest, perfect quality, original, amazing quality, masterpiece, very awa" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
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README.md
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@@ -69,6 +69,10 @@ After a while I finally got the hang of it. It's actually much simpler than I ex
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just adding *detailed decoration* and *detailed room* should suffice. I thought I had made a mistake by not training it with same types of rooms instead of
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general and varied environments. Actually that was what make it works easier than expected.
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just adding *detailed decoration* and *detailed room* should suffice. I thought I had made a mistake by not training it with same types of rooms instead of
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general and varied environments. Actually that was what make it works easier than expected.
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And as for people, no need to really add 1boy or 1girl, unless that's exactly the number you want, just adding *mini people* suffice. I forgot that I
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added as caption such tag as well as *mini world*. Also even if it won't be visible, adding a background, as *forest background* improves the quality a lot. So,in short,
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this LoRA works differently from many isometric LoRAs (or not?)
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