Instructions to use Tinsae/copper1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Tinsae/copper1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tinsae/copper1", 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:
- 5becdf0e110c8ac00c669db9e5ea939e967a92ccac1be97472b4f8cf71aea753
- Size of remote file:
- 246 MB
- SHA256:
- 089b03ad9513a6f380bd6d2505b52f76e296efb7ab6656b17969d5ba779853d2
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