Instructions to use D4ve-R/yellow-lora-sd15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use D4ve-R/yellow-lora-sd15 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("D4ve-R/yellow-lora-sd15") 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:
- 1a75e65a512f01d83d2844a10f9bf159de6dd816b297ba08a3cf122ab39de005
- Size of remote file:
- 563 Bytes
- SHA256:
- c2eb9019c35cd07696067a1bb8f101cc9130df23642187a391b24cd8716b9141
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.