Instructions to use iamkaikai/amazing-logos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iamkaikai/amazing-logos with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("iamkaikai/amazing-logos", 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
Ctrl+K
- checkpoint-1000
- checkpoint-100000
- checkpoint-110000
- checkpoint-120000
- checkpoint-130000
- checkpoint-140000
- checkpoint-150000
- checkpoint-160000
- checkpoint-170000
- checkpoint-180000
- checkpoint-190000
- checkpoint-200000
- checkpoint-60000
- checkpoint-80000
- checkpoint-90000
- feature_extractor
- safety_checker
- scheduler
- text_encoder
- tokenizer
- unet
- vae
- 1.57 kB
- 1.83 kB
- 3.85 GB xet
- 3.85 GB xet
- 1.8 MB xet
- 635 Bytes
- 200 kB