Instructions to use Floncer/projecteee with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Floncer/projecteee with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Floncer/projecteee", 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
- Xet hash:
- 9ea84c87a3f4d4d71beaa1bf94dc3f531c474efbf695b241b5de360b06b82375
- Size of remote file:
- 8.04 GB
- SHA256:
- 1c1c66c8c05c4bb6764a40f0fa52156dc0818a46fee29e197b0d92d88c6d757f
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