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
File size: 277 Bytes
a5682ef | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | 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()
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