Instructions to use datumo/CAC-CoT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datumo/CAC-CoT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="datumo/CAC-CoT")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("datumo/CAC-CoT") model = AutoModel.from_pretrained("datumo/CAC-CoT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 814bce1981abd5e6892e72d4e793a9c2d0da6e17e10672254626ff0fbbe1ef5e
- Size of remote file:
- 2.18 GB
- SHA256:
- d6b8133c5ef906aed8691bc5c494fc8cebad9e0e91da4a379581ffbcdc36e665
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