Instructions to use sam11113/lll with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sam11113/lll with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Phr00t/Qwen-Image-Edit-Rapid-AIO", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("sam11113/lll") prompt = "UNICODE\u0000\u0000 \u0000 \u0000B\u0000e\u0000u\u0000t\u0000y\u0000(\u0000s\u0000c\u0000o\u0000r\u0000e\u0000_\u00009\u0000,\u0000 \u0000s\u0000c\u0000o\u0000r\u0000e\u0000_\u00008\u0000_\u0000u\u0000p\u0000,\u0000 \u0000s\u0000c\u0000o\u0000r\u0000e\u0000_\u00007\u0000_\u0000u\u0000p\u0000:\u00001\u0000.\u00008\u0000)\u0000,\u0000 \u0000r\u0000a\u0000t\u0000i\u0000n\u0000g\u0000_\u0000s\u0000a\u0000f\u0000e\u0000,\u0000 \u0000r\u0000a\u0000t\u0000i\u0000n\u0000g\u0000_\u0000e\u0000x\u0000p\u0000l\u0000i\u0000c\u0000i\u0000t\u0000,\u0000n\u0000s\u0000f\u0000w\u0000,\u0000r\u0000e\u0000a\u0000d\u0000 \u0000d\u0000e\u0000s\u0000c\u0000r\u0000i\u0000p\u0000t\u0000i\u0000o\u0000n\u0000,\u0000 \u0000l\u0000o\u0000o\u0000k\u0000i\u0000n\u0000g\u0000 \u0000f\u0000o\u0000r\u0000 \u0000a\u0000 \u0000v\u0000i\u0000e\u0000w\u0000e\u0000r\u0000,\u0000 \u0000i\u0000n\u0000 \u0000a\u0000 \u0000c\u0000o\u0000s\u0000t\u0000u\u0000m\u0000e\u0000" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download Lulu-000005.safetensors from sam11113/lll: direct link, hf CLI and curl.
- Browser
- Download file 228 MB
-
https://huggingface.co/sam11113/lll/resolve/main/Lulu-000005.safetensors
- Command line
-
hf download hf://sam11113/lll/Lulu-000005.safetensors
-
curl -L -o Lulu-000005.safetensors https://huggingface.co/sam11113/lll/resolve/main/Lulu-000005.safetensors
228 MB
- Xet hash:
- 479e1d80909dffea2917ccf79edae1aa38521de0cf2f970aab776fd632f51f1c
- Size of remote file:
- 228 MB
- SHA256:
- 5ed9a4cbb3c47398b75436f21a430ebcb842dbcd912b9b702115c0b74cf0b314
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