Instructions to use OpenNLG/OpenBA-V1-Code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenNLG/OpenBA-V1-Code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="OpenNLG/OpenBA-V1-Code", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenNLG/OpenBA-V1-Code", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c1f1864b27861bebcedd4d4fa152dfaa2f2fa3fcbee6ecbd334636a7a190a15
- Size of remote file:
- 9.96 GB
- SHA256:
- 6c331b78b1a2b2d7e16b13e8155bb50ffd50ffd045a51cda80921d82b7de7803
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