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 youngexlance/Vatarstilfly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LongCat-Video-Avatar 1.5
How to use youngexlance/Vatarstilfly 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 youngexlance/Vatarstilfly with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("youngexlance/Vatarstilfly", 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 youngexlance/Vatarstilfly with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("youngexlance/Vatarstilfly", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 223c705cdd7c01435d3e73b55e77060973eb7a60b6c7bc8e645ab216d7af381e
- Size of remote file:
- 2.52 GB
- SHA256:
- d969115a7f3fbc212a277ed4399f77a1a065d170148c6d4bc272e980cd3e907a
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