LongCat-Video-Avatar 1.5
ONNX
Diffusers
Safetensors
Transformers
English
Chinese
audio-text-to-video
audio-image-text-to-video
audio-driven-video-continuation
avatar
video-generation
Instructions to use smartdigitalnetworks/LongCat-Video-Avatar-1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LongCat-Video-Avatar 1.5
How to use smartdigitalnetworks/LongCat-Video-Avatar-1.5 with LongCat-Video-Avatar 1.5:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Diffusers
How to use smartdigitalnetworks/LongCat-Video-Avatar-1.5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("smartdigitalnetworks/LongCat-Video-Avatar-1.5", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Transformers
How to use smartdigitalnetworks/LongCat-Video-Avatar-1.5 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("smartdigitalnetworks/LongCat-Video-Avatar-1.5", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a05dab580fe338218e820c20e906df5a2b724de76c3ca9b555854ed9898c85f
- Size of remote file:
- 3.09 GB
- SHA256:
- a8e94b85976e5864ba3e9525c7e6c83b2a1eca42d4b797a0c7c24d778e40fd95
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.