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
Download random_states_0.pkl from JingyeChen22/textdiffuser2-full-ft-inpainting: direct link, hf CLI and curl.
- Browser
- Download file 21.8 kB
-
https://huggingface.co/JingyeChen22/textdiffuser2-full-ft-inpainting/resolve/main/random_states_0.pkl
- Command line
-
hf download hf://JingyeChen22/textdiffuser2-full-ft-inpainting/random_states_0.pkl
-
curl -L -o random_states_0.pkl https://huggingface.co/JingyeChen22/textdiffuser2-full-ft-inpainting/resolve/main/random_states_0.pkl
21.8 kB
- Xet hash:
- b5f0fd7200e06eb3631943afc9ccb85c5bc617da2b81d6c60188a3438227a00e
- Size of remote file:
- 21.8 kB
- SHA256:
- c4ca69111f4fcd38dd9730005a681b337185069c10cd95c59c78b33a01eb4b23
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