Instructions to use VuDucQuang/landscape-style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VuDucQuang/landscape-style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("VuDucQuang/landscape-style", 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 text_encoder/pytorch_model.bin from VuDucQuang/landscape-style: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/VuDucQuang/landscape-style/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://VuDucQuang/landscape-style/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/VuDucQuang/landscape-style/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 5442ee178ceec29614201ef05df64831de3bd039d17e938e6a6c0fd435d2991d
- Size of remote file:
- 492 MB
- SHA256:
- 8d4ef705b00395cb423b125c5ca6851ea46382f1a68e18beca35fd4663fc527d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.