Instructions to use JingyeChen22/textdiffuser2-full-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JingyeChen22/textdiffuser2-full-ft with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JingyeChen22/textdiffuser2-full-ft", 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 link to paper, tags
#1
by nielsr HF Staff - opened
Hi @JingyeChen22 congrats on the ECCV Oral!
This PR ensures the model can be viewed from https://huggingface.co/papers/2311.16465 and adds the appropriate tag.
Btw if possible, would be awesome to make https://github.com/microsoft/unilm/blob/master/textdiffuser-2/data/layout_planner_data_5k.json available as a HF dataset.
See here for a guide: https://huggingface.co/docs/datasets/loading. We can then also link it to the paper.