Instructions to use smeoni/apericube with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smeoni/apericube with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="smeoni/apericube")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("smeoni/apericube") model = AutoModel.from_pretrained("smeoni/apericube") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95aa6f698309956343ddec5f88f687d0118319b319c28d1696a0ed329e2612c6
- Size of remote file:
- 1.71 MB
- SHA256:
- bc84ec51870da75c7bd83a3bac7a73b340e1a6f6aff255c8c3745072668aeccd
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