Instructions to use rain1011/Video-LaVIT-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rain1011/Video-LaVIT-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rain1011/Video-LaVIT-v1", 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 visual_tokenizer/highres_tokenizer_decoder.bin from rain1011/Video-LaVIT-v1: direct link, hf CLI and curl.
- Browser
- Download file 830 MB
-
https://huggingface.co/rain1011/Video-LaVIT-v1/resolve/main/visual_tokenizer/highres_tokenizer_decoder.bin
- Command line
-
hf download hf://rain1011/Video-LaVIT-v1/visual_tokenizer/highres_tokenizer_decoder.bin
-
curl -L -o highres_tokenizer_decoder.bin https://huggingface.co/rain1011/Video-LaVIT-v1/resolve/main/visual_tokenizer/highres_tokenizer_decoder.bin
830 MB
- Xet hash:
- bdaf1f3cdada17698ee5853f4da955fc9d60ce3f7f81142e87a44cbd21f8dbc1
- Size of remote file:
- 830 MB
- SHA256:
- ed7a1dd1bcd485fba789aab939e20859ae1a33f3110ae9bddc3b9270b0158ba9
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