Instructions to use tmtmtm45/g33-lokr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tmtmtm45/g33-lokr with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("tmtmtm45/g33-lokr") prompt = "g3f, portrait, both arms down, indoor window light" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
g33-lokr β Krea 2 character LoKR
Character LoKR for Krea 2, trained on Krea-2-Raw (1500 steps, LoKR factor 4, 33 images).
Use with Krea-2-Turbo for inference.
Trigger
g3f
Strength
Start around 0.6β0.9.
Files
pytorch_lora_weights.safetensorsβ final adapter (~5.4 MB)sample_*.jpgβ step-1500 previews
Use with Diffusers / Krea 2 Turbo
import torch
from diffusers import Krea2Pipeline
pipe = Krea2Pipeline.from_pretrained(
"krea/Krea-2-Turbo",
torch_dtype=torch.bfloat16,
).to("cuda")
pipe.load_lora_weights("tmtmtm45/g33-lokr")
image = pipe(
"g3f, portrait, soft window light",
num_inference_steps=8,
guidance_scale=0.0,
).images[0]
image.save("out.png")
ComfyUI
Drop into your Krea2 LoRAs folder and prompt with g3f.
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Model tree for tmtmtm45/g33-lokr
Base model
krea/Krea-2-Raw