Instructions to use ethers/avril15s02-lora-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ethers/avril15s02-lora-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ethers/avril15s02-lora-model") 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:
- 5a53d3e12fc8467aeb8126fbb58065c4f57cb6c88b0f6a7c460c8e29bdd60bb9
- Size of remote file:
- 6.59 MB
- SHA256:
- f3ef48b7d82e37780f417b18c87d9efc808a697ba875ce58c251b661eb3a767c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.