Feature Extraction
Transformers
Safetensors
PyTorch
liquid_codec
audio
audio-codec
bfloat16
custom_code
Instructions to use LiquidAI/Liquid-Codec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiquidAI/Liquid-Codec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LiquidAI/Liquid-Codec", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LiquidAI/Liquid-Codec", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
3 days ago
-
Initial commit
Co-authored-by: orech <orech@users.noreply.huggingface.co>1150afc