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-8000/scheduler.bin from ethers/sd-loral-cat-model: direct link, hf CLI and curl.
- Browser
- Download file 563 Bytes
-
https://huggingface.co/ethers/sd-loral-cat-model/resolve/main/checkpoint-8000/scheduler.bin
- Command line
-
hf download hf://ethers/sd-loral-cat-model/checkpoint-8000/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/ethers/sd-loral-cat-model/resolve/main/checkpoint-8000/scheduler.bin
563 Bytes
- Xet hash:
- 93fd635217f812984c53ee13c262aad54dc522e842cd836e5e462736bc24cb56
- Size of remote file:
- 563 Bytes
- SHA256:
- d7d4a616bb5c26eb0ee0c3a02d41cd8abede8d170071d3c524d77e5474600053
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