Instructions to use JingyeChen22/textdiffuser2-full-ft-inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JingyeChen22/textdiffuser2-full-ft-inpainting 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-inpainting", 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
- Xet hash:
- a1784e0ffb25a2d9bfb53b77950a6edddf2a5efb16559a96cbe671614c995902
- Size of remote file:
- 627 Bytes
- SHA256:
- 6833b1c75c51ce0812d0e9bd99c70f8153e4eaf0481ad606ac770f03ec7e6126
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