Instructions to use Teradata/codesage-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Teradata/codesage-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Teradata/codesage-small", trust_remote_code=True)# Load model directly from transformers import CodeSage model = CodeSage.from_pretrained("Teradata/codesage-small", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1b552f033427acc88195ab966259fd0d69d9595f15bc44955cd91962172a843
- Size of remote file:
- 512 MB
- SHA256:
- 598d2277f44d871de5c1baa9f553e5541e3b8cfe72385bd2535fa954ca4f06c0
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