Instructions to use SimianLuo/LCM_Dreamshaper_v7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SimianLuo/LCM_Dreamshaper_v7 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SimianLuo/LCM_Dreamshaper_v7", dtype=torch.bfloat16, device_map="cuda") 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 vae_decoder/model.onnx from SimianLuo/LCM_Dreamshaper_v7: direct link, hf CLI and curl.
- Browser
- Download file 198 MB
-
https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7/resolve/main/vae_decoder/model.onnx
- Command line
-
hf download hf://SimianLuo/LCM_Dreamshaper_v7/vae_decoder/model.onnx
-
curl -L -o model.onnx https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7/resolve/main/vae_decoder/model.onnx
198 MB
- Xet hash:
- 3eeaeac5d79ffe3ac900e926c9de6a9cfabca658137afdee8481123b8fcc9ab2
- Size of remote file:
- 198 MB
- SHA256:
- 0ea3df9f76ff9de5cea29106f246bf9b71297d418b013404f91dae5a0ddba98e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.