Instructions to use ZibinDong/ActionCodec-Base-RVQft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZibinDong/ActionCodec-Base-RVQft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ZibinDong/ActionCodec-Base-RVQft", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZibinDong/ActionCodec-Base-RVQft", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f46166cdf4c1107d7c59535686d7db91967aa2a75aa847923518f2ebe157e1d0
- Size of remote file:
- 197 MB
- SHA256:
- ca503eb143d24514bc452fa05f121af5112c579d81f324f563698f32cd383342
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