Instructions to use Samffprice/dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Samffprice/dev with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Samffprice/dev", 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:
- 9bca9e72d454541c0ac5949b45833fc33d55dd082eaca1d74e247741f711f78c
- Size of remote file:
- 109 MB
- SHA256:
- e6543730f6459b168f710ddde1880cc4b4455f1a4a6895534adee1f6c3276e58
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