Instructions to use recoilme/temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use recoilme/temp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("recoilme/temp", 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:
- a8f18c993a46a45b91c137a425d336fa33d4112d31b510bf40ccbbac42839f3b
- Size of remote file:
- 6.32 GB
- SHA256:
- 0e522c9ff4c6f9d7d8de6870349698af5f116312a60fcf5eaa05ba714fbd55f7
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