Instructions to use JiaxinGe/Diffusers-BAGEL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JiaxinGe/Diffusers-BAGEL with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JiaxinGe/Diffusers-BAGEL", 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": "BagelPipeline", | |
| "_diffusers_version": "0.34.0", | |
| "bagel_model": [ | |
| "pipeline", | |
| "Bagel" | |
| ], | |
| "latent_patch_size": 2, | |
| "tokenizer": [ | |
| "pipeline", | |
| "Qwen2Tokenizer" | |
| ], | |
| "vae": [ | |
| "pipeline", | |
| "AutoEncoder" | |
| ], | |
| "vit_max_num_patch_per_side": 70 | |
| } | |