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
- Draw Things
- DiffusionBee
- Xet hash:
- ab35831b89e6a1ebe369e00ae2f8d641dbb44fa9bcad5b64e65c5d5867cac13a
- Size of remote file:
- 3.29 MB
- SHA256:
- c3c807f2e6c8a4454fbd6badad4d44bd1160d225a839d1dc8ea53371b61f52ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.