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/pytorch_model.bin from ethers/sd-loral-cat-model: direct link, hf CLI and curl.
- Browser
- Download file 3.29 MB
-
https://huggingface.co/ethers/sd-loral-cat-model/resolve/main/checkpoint-8000/pytorch_model.bin
- Command line
-
hf download hf://ethers/sd-loral-cat-model/checkpoint-8000/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ethers/sd-loral-cat-model/resolve/main/checkpoint-8000/pytorch_model.bin
3.29 MB
- Xet hash:
- 8ecb03320c89f9b1ff72593a084d88f5093c47ceff1f4a61fbe1086138aa2b4e
- Size of remote file:
- 3.29 MB
- SHA256:
- ac72c3c94f263ec1131b26dccce4c65517c58d5d78e7b4632ed02261efa278ba
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