Instructions to use Rita7th/Luminastra_XL_Model_Storage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Rita7th/Luminastra_XL_Model_Storage with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Rita7th/Luminastra_XL_Model_Storage", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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> (worst quality, normal quality, low quality:1.2), interlocked fingers, extra digit, bad fingers, (bad anatomy, bad),
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> lowres, jpeg artifacts, sketch, comic, monochrome, watermark, unfinished, oldest, artistic error, text, photorealistic, realistic, [abstract],
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> (worst quality, normal quality, low quality:1.2), interlocked fingers, extra digit, bad fingers, (bad anatomy, bad),
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> lowres, jpeg artifacts, sketch, comic, monochrome, watermark, unfinished, oldest, artistic error, text, photorealistic, realistic, [abstract],
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**Sampling method**
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