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
Ctrl+K
- extended-o1-10mm-16k-2bin-1p2ms
- extended-o1-10mm-1k-2bin-1p2ms
- extended-o1-10mm-2k-2bin-1p2ms
- extended-o1-10mm-4k-2bin-1p2ms
- extended-o1-10mm-8k-2bin-1p2ms
- extended-o1-1mm-16k-2bin-1p2ms
- extended-o1-1mm-2k-2bin-1p2ms
- extended-o1-1mm-4k-2bin-1p2ms
- extended-o1-1mm-8k-2bin-1p2ms
- extended-o1-5mm-16k-2bin-1p2ms
- extended-o1-5mm-1k-2bin-1p2ms
- extended-o1-5mm-2k-2bin-1p2ms
- extended-o1-5mm-4k-2bin-1p2ms
- extended-o1-5mm-8k-2bin-1p2ms
- extended-o2-10mm-16k-2bin-1p2ms
- extended-o2-10mm-1k-2bin-1p2ms
- extended-o2-10mm-2k-2bin-1p2ms
- extended-o2-10mm-4k-2bin-1p2ms
- extended-o2-10mm-8k-2bin-1p2ms
- extended-o2-1mm-16k-2bin-1p2ms
- extended-o2-1mm-2k-2bin-1p2ms
- extended-o2-1mm-4k-2bin-1p2ms
- extended-o2-1mm-8k-2bin-1p2ms
- extended-o2-5mm-16k-2bin-1p2ms
- extended-o2-5mm-1k-2bin-1p2ms
- extended-o2-5mm-2k-2bin-1p2ms
- extended-o2-5mm-4k-2bin-1p2ms
- extended-o2-5mm-8k-2bin-1p2ms
- paper-o1-5mm-4k-2bin-1p2ms
- paper-o2-5mm-4k-2bin-1p2ms
- sparse-o1-5mm-4k-21bin-1p2ms
- sparse-o1-5mm-4k-21bin-2ms
- sparse-o1-5mm-4k-2bin-1p2ms
- sparse-o1-5mm-4k-2bin-2ms