Instructions to use svjack/CogvideoX-Interpolation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use svjack/CogvideoX-Interpolation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("svjack/CogvideoX-Interpolation", 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
Download configuration.json from svjack/CogvideoX-Interpolation: direct link, hf CLI and curl.
- Browser
- Download file 47 Bytes
-
https://huggingface.co/svjack/CogvideoX-Interpolation/resolve/5a735d2bdb851e2f68246ca5ecce79321e96f976/configuration.json
- Command line
-
hf download hf://svjack/CogvideoX-Interpolation@5a735d2bdb851e2f68246ca5ecce79321e96f976/configuration.json
-
curl -L -o configuration.json https://huggingface.co/svjack/CogvideoX-Interpolation/resolve/5a735d2bdb851e2f68246ca5ecce79321e96f976/configuration.json
47 Bytes
| {"framework":"Pytorch","task":"image-to-video"} |