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
Usage
#1
by Mousey - opened
Hi Kaikai, great work, however, I am not really able to run it or I'm not sure I'm doing that right.
pipe = DiffusionPipeline.from_pretrained(
pretrained_model_name_or_path,
torch_dtype=torch.float16
).to("cuda")
gives an error, so I had to add low_cpu_mem_usage=False to it. Then it runs but the results are not equal to the ones you are getting here. Any ideas ?
Hi Mousey,
thanks for asking. From the infomation given, I can't really tell what's going wrong. Usually, the problem has to do with memory. But, if you can run the model, I suspect the problem has to do with the prompt. Did you use the template keywords before and after in the prompt?