Instructions to use aa-studio/aa_studio_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aa-studio/aa_studio_data with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aa-studio/aa_studio_data", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| /** | |
| * Changes the background color of the canvas. | |
| * | |
| * @method updateBackground | |
| * @param {image} String | |
| * @param {clearBackgroundColor} String | |
| * @ | |
| */ | |
| LGraphCanvas.prototype.updateBackground = function (image, clearBackgroundColor) { | |
| this._bg_img = new Image(); | |
| this._bg_img.name = image; | |
| this._bg_img.src = image; | |
| this._bg_img.onload = () => { | |
| this.draw(true, true); | |
| }; | |
| this.background_image = image; | |
| this.clear_background = true; | |
| this.clear_background_color = clearBackgroundColor; | |
| this._pattern = null | |
| } | |