Instructions to use vidfom/lt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vidfom/lt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vidfom/lt", 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
File size: 513 Bytes
8c6346f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | #!/bin/bash
# Replace <repository_url> with your GitHub repository URL
REPO_URL="https://github.com/unitconvert/Model-.git"
# Navigate to the directory containing your pages
cd "D:/modle/LTX-Video-gradio-ui" || exit
# Initialize a Git repository if not already initialized
if [ ! -d ".git" ]; then
git init
git remote add origin "$REPO_URL"
git checkout -b gh-pages
fi
# Add all files, commit, and push to gh-pages branch
git add .
git commit -m "Update pages"
git push origin gh-pages |