Instructions to use jinofcoolnes/syntheticcmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jinofcoolnes/syntheticcmodel with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jinofcoolnes/syntheticcmodel", 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
Commit History
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Add `scale_factor` to vae config. (#2)
- Add `scale_factor` to vae config. (f2955055a951da058e3e3bda89becbb93c509fbd) Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>4d649e4
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Add Diffusers weights (#1)
- Add Diffusers weights (0bbee018767b68c65b381fe9dd03fcadcc6e3e24)90c8f6b
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Upload comodel2.yaml
yamld7e8c5b
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Upload comodel2.ckpt
035878d -
initial commit
2d651c4