Instructions to use jjbascunan/Django_Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jjbascunan/Django_Python with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jjbascunan/Django_Python", 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
| license: openrail | |
| datasets: | |
| - proj-persona/PersonaHub | |
| language: | |
| - es | |
| library_name: diffusers | |
| tags: | |
| - code | |
| - art | |