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:
- 81e36256bedb3c4085b6cb2348a90138901e33b741d25425eff566b7a6d2a2f9
- Size of remote file:
- 1.18 GB
- SHA256:
- 630ca774672856d2e0e39a702e590f635a1cfc5726a64b6578ab46dd367369a9
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