Instructions to use JingyeChen22/textdiffuser2-lora-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JingyeChen22/textdiffuser2-lora-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-lora-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
- Xet hash:
- 85849e944f02ae2ab963920aff2e91bf15402af0de8b8b8496642613efb5b24b
- Size of remote file:
- 499 MB
- SHA256:
- 9d0aca9a53a011d992c47389f7bf85329182f4e3f15c9eedc8bb31de77a168cf
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