Instructions to use Danielbsittler/Jb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Danielbsittler/Jb with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wikeeyang/Magic-Wan-Image-V2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Danielbsittler/Jb") prompt = "ASCII\u0000\u0000\u0000Screenshot" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 372 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/IMG_1672.jpeg
text: "ASCII\0\0\0Screenshot"
base_model: wikeeyang/Magic-Wan-Image-V2
instance_prompt: null
---
# Jb
<Gallery />
## Model description
Works
## Download model
[Download](/Danielbsittler/Jb/tree/main) them in the Files & versions tab.
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