Instructions to use cyuzhang/rank4_lr4_batch4_30k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cyuzhang/rank4_lr4_batch4_30k 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("cyuzhang/rank4_lr4_batch4_30k") 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:
- 6baea5f0eaaf9d5695a309b38386e323a2b2f092218566e1897da5b1ecfaefcd
- Size of remote file:
- 6.6 MB
- SHA256:
- 20be35c234e4d753cef11a583d213b0a9eb3954e64269a0b70513fadb79198f6
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