Instructions to use Glanty/Capybara with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Glanty/Capybara with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Glanty/Capybara", 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
| { | |
| "_class_name": "FluxPriorReduxPipeline", | |
| "_diffusers_version": "0.32.0.dev0", | |
| "feature_extractor": [ | |
| "transformers", | |
| "SiglipImageProcessor" | |
| ], | |
| "image_embedder": [ | |
| "flux", | |
| "ReduxImageEncoder" | |
| ], | |
| "image_encoder": [ | |
| "transformers", | |
| "SiglipVisionModel" | |
| ] | |
| } | |