Instructions to use EeeeeeeH/Trial2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EeeeeeeH/Trial2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EeeeeeeH/Trial2", 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
- Xet hash:
- 67fbb34580b2ce8b7ab20d22acb8f092afe82d9ecff7953eeecd680e8594aaee
- Size of remote file:
- 455 MB
- SHA256:
- a98f56e23a449a8424b54c732b3d2f5af72774752f2579d1ed1bf8911c2c3023
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