Instructions to use naclbit/trinart_stable_diffusion_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use naclbit/trinart_stable_diffusion_v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("naclbit/trinart_stable_diffusion_v2", 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
Commit History
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Add `clip_sample=False` to scheduler to make model compatible with DDIM. (#12)
- Add `clip_sample=False` to scheduler to make model compatible with DDIM. (27b81cc771f37d052007ad57d33c59568ee8912c) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>61e59b3
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Add DIffusers weights (#9)
- Add Diffusers weights for trinart2_step60000.ckpt (3ac53b52933af1182c1fb29a61802042dab71cc0)15f8aed