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
File size: 508 Bytes
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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")
``` |