Instructions to use Teradata/codesage-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Teradata/codesage-base-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Teradata/codesage-base-v2", trust_remote_code=True)# Load model directly from transformers import CodeSage model = CodeSage.from_pretrained("Teradata/codesage-base-v2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb6f22d4a6c8e8e1c28ff8d3466277e98e219d18d3735fc12d793b79d6e918c6
- Size of remote file:
- 358 MB
- SHA256:
- de08d046cce2f16c9fbfce011a75e77585ebc47412c1531659c3b53b9ed58b5e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.