Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
textual_inversion
Instructions to use dxli/fancy_boot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dxli/fancy_boot with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_textual_inversion("dxli/fancy_boot") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 0bea08b035256146906026e84c8946859181e13e3de1349699a31636a8a9d4c8
- Size of remote file:
- 492 MB
- SHA256:
- 13697bca0560da4794c3481125c6c031ac28b4b62b3fc8a7ba40e0145d6c3565
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.