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-3500/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-3500/optimizer.bin
- Command line
-
hf download hf://ethers/sd-loral-cat-model/checkpoint-3500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/ethers/sd-loral-cat-model/resolve/main/checkpoint-3500/optimizer.bin
6.59 MB
- Xet hash:
- 562915cd85e99a57a403e73aebcfee4ea7131d33606cdc450090a447b1c7cd83
- Size of remote file:
- 6.59 MB
- SHA256:
- 8999547edc7568e3e4175618ab594c4aebd89109d99a4c36cab369644aeb0f2c
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