Instructions to use Shriramnag/Shiv-AI-Video-Generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shriramnag/Shiv-AI-Video-Generator with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Shriramnag/Shiv-AI-Video-Generator", 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
| from transformers import HfArgumentParser | |
| from ltx_video.inference import infer, InferenceConfig | |
| def main(): | |
| parser = HfArgumentParser(InferenceConfig) | |
| config = parser.parse_args_into_dataclasses()[0] | |
| infer(config=config) | |
| if __name__ == "__main__": | |
| main() | |