Instructions to use ZibinDong/ActionCodec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZibinDong/ActionCodec2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZibinDong/ActionCodec2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 452 Bytes
1bfc3f0 | 1 2 3 4 5 6 7 8 9 | """Shared physical models, layouts, and dense and sparse routers."""
from .configuration import ActionCodec2Config, ConfigError
from .presets import ComponentSpec, PresetConfig
from .processor import ActionCodec2Processor
from .routing import ActionCodec2Router
from .trajectory import ActiveTrajectory
__all__ = ["ActionCodec2Config", "ConfigError", "ComponentSpec", "PresetConfig", "ActionCodec2Processor", "ActionCodec2Router", "ActiveTrajectory"]
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