Instructions to use Hishambarakat/checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Hishambarakat/checkpoint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Hishambarakat/checkpoint", 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
Ctrl+K
- IPAdapter
- Whl
- engine
- flux
- nvidia
- pony
- root
- scheduler
- sd15
- sdxl-lightning
- sdxl
- stable-diffusion-xl-base-1.0
- tokenizer
- tokenizer_2
- trt
- unet
- vae
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