Instructions to use CIawevy/SD3.5M-TextPecker-SQPA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CIawevy/SD3.5M-TextPecker-SQPA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CIawevy/SD3.5M-TextPecker-SQPA", torch_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: add metadata, paper link, and license
#1
by nielsr HF Staff - opened
Hi! I'm Niels, part of the Hugging Face community science team. This PR aims to improve the model card for this repository by adding missing metadata (pipeline tag, license, and library name) and linking it to the associated research paper and GitHub repository. This helps other researchers find and use your work more effectively.
CIawevy changed pull request status to merged