Instructions to use personal1802/36 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use personal1802/36 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("latent-consistency/lcm-lora-sdv1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("personal1802/36") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from personal1802/36: direct link, hf CLI and curl.
- Browser
- Download file 406 Bytes
-
https://huggingface.co/personal1802/36/resolve/main/README.md
- Command line
-
hf download hf://personal1802/36/README.md
-
curl -L -o README.md https://huggingface.co/personal1802/36/resolve/main/README.md
406 Bytes
metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: '-'
output:
url: images/WHITE.png
base_model: latent-consistency/lcm-lora-sdv1-5
instance_prompt: null
CattleyaMix

- Prompt
- -
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.