Instructions to use B4100/readyforbj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use B4100/readyforbj with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TheRaf7/ultra-real-wan2.2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("B4100/readyforbj") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
File size: 667 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/adaaff0a-f617-4617-8c75-cdfbfe2e1fdb.jpeg
text: '-'
base_model: TheRaf7/ultra-real-wan2.2
instance_prompt: null
---
# ready4bj
<Gallery />
## Model description
A woman walks toward the viewer. She pulls her hair back and holds it up with both hands. She gets down on her knees.
A woman walks toward the viewer. She pulls her hair back and holds it up with both hands. She gets down on her knees. Then she opens her mouth wide and extends her tongue.
## Download model
[Download](/B4100/readyforbj/tree/main) them in the Files & versions tab.
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