Instructions to use sohancec/Desi-Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sohancec/Desi-Lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RunDiffusion/Juggernaut-XL-v9", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("sohancec/Desi-Lora") prompt = "UNICODE\u0000\u0000U\u0000l\u0000t\u0000r\u0000a\u0000 \u0000h\u0000i\u0000g\u0000h\u0000 \u0000d\u0000e\u0000t\u0000a\u0000i\u0000l\u0000,\u0000 \u0000 \u0000u\u0000l\u0000t\u0000r\u0000a\u0000 \u0000h\u0000i\u0000g\u0000h\u0000 \u0000q\u0000u\u0000a\u0000l\u0000i\u0000t\u0000y\u0000,\u0000 \u0000M\u0000a\u0000s\u0000t\u0000e\u0000r\u0000p\u0000i\u0000e\u0000c\u0000e\u0000,\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000r\u0000e\u0000a\u0000l\u0000i\u0000s\u0000t\u0000i\u0000c\u0000,\u0000 \u0000q\u0000u\u0000a\u0000l\u0000i\u0000t\u0000y\u0000,\u0000 \u0000b\u0000e\u0000s\u0000t\u0000 \u0000d\u0000e\u0000t\u0000a\u0000i\u0000l\u0000,\u0000 \u0000C\u0000o\u0000l\u0000l\u0000a\u0000p\u0000s\u0000e\u0000d\u0000 \u0000s\u0000k\u0000y\u0000s\u0000c\u0000r\u0000a\u0000p\u0000e\u0000r\u0000 \u0000r\u0000u\u0000i\u0000n\u0000s\u0000,\u0000 \u0000b\u0000u\u0000r\u0000n\u0000i\u0000n\u0000g\u0000 \u0000c\u0000i\u0000t\u0000y\u0000r\u0000u\u0000i\u0000n\u0000s\u0000,\u0000 \u0000m\u0000a\u0000s\u0000s\u0000i\u0000v\u0000e\u0000 \u0000c\u0000i\u0000t\u0000y\u0000r\u0000u\u0000i\u0000n\u0000s\u0000,\u0000 \u0000S\u0000c\u0000i\u0000f\u0000i\u0000 \u0000c\u0000i\u0000t\u0000y\u0000r\u0000u\u0000i\u0000n\u0000s\u0000,\u0000 \u0000" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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