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
Add metadata (pipeline tag, library, license)
#1
by nielsr HF Staff - opened
This PR improves the model card by adding essential metadata: pipeline_tag: any-to-any, library_name: diffusers, and license: apache-2.0. This ensures better discoverability on the Hugging Face Hub and provides clearer information about the model's capabilities and licensing.