Instructions to use Kwai-Kolors/CoTyle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kwai-Kolors/CoTyle with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Kwai-Kolors/CoTyle", 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 Settings
- Draw Things
- DiffusionBee
Improve model card: update pipeline tag, add library, and detailed content
#1
by nielsr HF Staff - opened
This PR significantly enhances the model card for Kwai-Kolors/CoTyle.
Key improvements include:
- Updated Metadata:
- Corrected the
pipeline_tagfromimage-text-to-texttotext-to-image, accurately reflecting the model's functionality (generating images from text prompts and a style code). - Added
library_name: diffusers, as the model is built upon and compatible with the Diffusers library, enabling better integration and discoverability on the Hub.
- Corrected the
- Comprehensive Content:
- Incorporated a detailed introduction, news, ToDo list, and the abstract directly from the paper's GitHub README.
- Included prominent links and badges to the paper, project page, Hugging Face demo, Hugging Face model, and the GitHub repository.
- Provided detailed "Quick Start" instructions, including environment setup, download steps, and command-line usage examples for both single and batch image generation, directly from the GitHub README.
- Added information about the Gradio app for local interactive inference.
- Included the full academic citation and acknowledgements.
This update makes the model card much more informative and user-friendly for anyone exploring the CoTyle model.
liuhuijie6410 changed pull request status to merged