Instructions to use lige/lige_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lige/lige_models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lige/lige_models", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
| license: agpl-3.0 | |
| language: | |
| - zh | |
| - en | |
| library_name: diffusers | |
| pipeline_tag: text-to-image | |
| tags: | |
| - stable-diffusion | |
| No paying, for sharing. | |
| 免费,共享。 | |
| 如果你喜欢这个项目,请点击喜欢。 | |
| If you like this project, please click like. | |
| link to github: https://github.com/ligerye/lige_models | |
| 你可以下载并使用这些模型,但是必须保证不用于任何盈利用途,该项目使用AGPL-V3许可证。 | |
| You can download and use these models, but you must ensure that they are not used for any profitable purpose. The project uses AGPL-V3 license. |