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
File size: 354 Bytes
f8bb229 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"_class_name": "FlowMatchDiscreteScheduler",
"_diffusers_version": "0.35.0",
"flux_base_shift": 0.5,
"flux_base_token": 256.0,
"flux_max_shift": 1.15,
"flux_max_token": 4096.0,
"flux_shift_factor": 1.0,
"n_tokens": null,
"num_train_timesteps": 1000,
"reverse": true,
"shift": 7.0,
"solver": "euler",
"use_flux_shift": false
}
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