Instructions to use XGGGV/DLRB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use XGGGV/DLRB 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-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("XGGGV/DLRB") prompt = "solo, 1girl, medium breasts, sitting on a chair, tube top, cargo pants, sneakers, cafe, wide shot,左手放在靠椅的把手上,右手拿着咖啡。 双腿翘腿坐在椅子上。 咖啡杯的材质是白色陶瓷并且带一点花纹,咖啡杯的尺寸偏小。木桌上放着吃剩的三明治。她眼睛看着外面的马路,背景是意大利。" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
DLRB

- Prompt
- solo, 1girl, medium breasts, sitting on a chair, tube top, cargo pants, sneakers, cafe, wide shot,左手放在靠椅的把手上,右手拿着咖啡。 双腿翘腿坐在椅子上。 咖啡杯的材质是白色陶瓷并且带一点花纹,咖啡杯的尺寸偏小。木桌上放着吃剩的三明治。她眼睛看着外面的马路,背景是意大利。
Model description
推荐Lora 1.2
Trigger words
You should use reba to trigger the image generation.
Download model
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