Instructions to use javismiles/dec3model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use javismiles/dec3model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("javismiles/dec3model") 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:
- cf3d31cda9f326202e90f55b80157b8aeedcf8c53824e33f6d0bc42a2cf508ff
- Size of remote file:
- 1 kB
- SHA256:
- ff5a0bba24eb0cee97b9e32eb12c64901e3b0d089e86a0b0613704a2cb676448
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