Instructions to use SJTU-DENG-Lab/Think-Then-Generate-T2I with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SJTU-DENG-Lab/Think-Then-Generate-T2I with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SJTU-DENG-Lab/Think-Then-Generate-T2I", 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
Add model card for Think-Then-Generate
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community team. I've opened this PR to add a comprehensive model card for the Think-Then-Generate model. This includes:
- Relevant metadata (
pipeline_tag,library_name) for improved discoverability. - Direct links to the paper, GitHub repository, project page, and Hugging Face Space.
- A summary of the 'Think-Then-Generate' paradigm and its methodology.
- The official installation instructions and sample inference command from the GitHub repository.
- The BibTeX citation.
Please let me know if any adjustments are needed. Thanks!