Instructions to use bytedance-research/RealCustom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bytedance-research/RealCustom with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bytedance-research/RealCustom", 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
- Local Apps
- Draw Things
- DiffusionBee
Add pipeline tag and library name, add sample usage
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Adding the
pipeline_tag: text-to-imageto enhance discoverability on the Hugging Face Hub. - Adding the
library_name: diffusersto enable the automated code snippet fordiffusers. - Including a Python sample usage snippet directly from the GitHub README for text-to-image generation.
CoreloneH changed pull request status to merged