Instructions to use Shriramnag/ShivAI-Image-to-Video with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shriramnag/ShivAI-Image-to-Video 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/ShivAI-Image-to-Video", 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
| [project] | |
| name = "ltx-core" | |
| version = "1.1.3" | |
| description = "Core implementation of Lightricks' LTX-2 model" | |
| readme = "README.md" | |
| requires-python = ">=3.10" | |
| dependencies = [ | |
| "torch~=2.7", | |
| "torchaudio", | |
| "einops", | |
| "numpy", | |
| "transformers>=4.52", | |
| "safetensors", | |
| "accelerate", | |
| "scipy>=1.14", | |
| ] | |
| [project.optional-dependencies] | |
| xformers = ["xformers"] | |
| fp8-trtllm = [ | |
| "tensorrt-llm==1.0.0", | |
| "onnx>=1.16.0,<1.20.0", | |
| "openmpi", | |
| ] | |
| [tool.uv] | |
| conflicts = [ | |
| [ | |
| { extra = "xformers" }, | |
| { extra = "fp8-trtllm" }, | |
| ], | |
| ] | |
| [tool.uv.sources] | |
| xformers = { index = "pytorch" } | |
| tensorrt-llm = { index = "nvidia" } | |
| [[tool.uv.index]] | |
| name = "pytorch" | |
| url = "https://download.pytorch.org/whl/cu129" | |
| explicit = true | |
| [[tool.uv.index]] | |
| name = "nvidia" | |
| url = "https://pypi.nvidia.com/" | |
| explicit = true | |
| [build-system] | |
| requires = ["uv_build>=0.9.8,<0.10.0"] | |
| build-backend = "uv_build" | |
| [dependency-groups] | |
| dev = [ | |
| "scikit-image>=0.25.2", | |
| ] | |