Instructions to use stillerman/trdne250 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stillerman/trdne250 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("stillerman/trdne250") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 938feec989ba0cd699c0f0a742e41df9564b6e199bdbd05fa959f4ec862cb575
- Size of remote file:
- 3.29 MB
- SHA256:
- 405c23a8bb866d20bdc8704d2d08b7bb722f9126499c393e9c784595fb4f51e8
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