Instructions to use lansinuote/diffusion.2.textual_inversion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lansinuote/diffusion.2.textual_inversion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lansinuote/diffusion.2.textual_inversion", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 3f11a93631e2e096743e6ce1ef74ebcff5a0b889a2cceb2c0bacc594fcf9034c
- Size of remote file:
- 492 MB
- SHA256:
- 9491c921cab0ea3294590700d448823f352d335f28e22e45f808c9f7467b700c
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