Instructions to use Dipl0/pepe-diffuser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Dipl0/pepe-diffuser with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Dipl0/pepe-diffuser", 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
| library_name: diffusers | |
| pipeline_tag: text-to-image | |
| tags: | |
| - pepe | |
| # How to use | |
| ***To prompt you can use the following code*** | |
| ```python | |
| from diffusers import StableDiffusionPipeline | |
| model_path = "Dipl0/pepe-diffuser" | |
| pipe = StableDiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float16) | |
| pipe.to("cuda") | |
| prompt = "pepe surfing on the moon" | |
| image = pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0] | |
| image.save(prompt.replace(" ","_") + ".png") | |
| ``` |