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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenNLG/OpenBA-V1-Code", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download __init__.py from OpenNLG/OpenBA-V1-Code: direct link, hf CLI and curl.
- Browser
- Download file 252 Bytes
-
https://huggingface.co/OpenNLG/OpenBA-V1-Code/resolve/main/__init__.py
- Command line
-
hf download hf://OpenNLG/OpenBA-V1-Code/__init__.py
-
curl -L -o __init__.py https://huggingface.co/OpenNLG/OpenBA-V1-Code/resolve/main/__init__.py
252 Bytes
| from .modeling_openba import OpenBAForConditionalGeneration | |
| from .configuration_openba import OpenBAConfig | |
| from .tokenization_openba import OpenBATokenizer | |
| __all__ = [ | |
| "OpenBAForConditionalGeneration", | |
| "OpenBAConfig", | |
| "OpenBATokenizer", | |
| ] |