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:
- 7f925c3a22b59e8c0fd3193d6c420092ddd3d0ec945966b1e1a225d90ffee95f
- Size of remote file:
- 4.93 GB
- SHA256:
- 105754241c5de1dcde2d94e2b07bda440624b866b2e1e398cd43b2ed389b7f6d
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