Instructions to use ethers/sd-loral-cat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ethers/sd-loral-cat-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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ethers/sd-loral-cat-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
Download checkpoint-5000/optimizer.bin from ethers/sd-loral-cat-model: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/ethers/sd-loral-cat-model/resolve/main/checkpoint-5000/optimizer.bin
- Command line
-
hf download hf://ethers/sd-loral-cat-model/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/ethers/sd-loral-cat-model/resolve/main/checkpoint-5000/optimizer.bin
6.59 MB
- Xet hash:
- c4150c6b6c5d1b83568ac346a452700718d2ae6f1c0c5dcd9becbdedc4a9c919
- Size of remote file:
- 6.59 MB
- SHA256:
- 18ddf3d15f2723b8086eebe4fac7db0dcfbe2228fd6432fea2c0aabf56d69d9f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.