Instructions to use XQ112/OpCodeBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use XQ112/OpCodeBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="XQ112/OpCodeBERT")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("XQ112/OpCodeBERT") model = AutoModel.from_pretrained("XQ112/OpCodeBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| base_model: | |
| - microsoft/unixcoder-base | |
| datasets: | |
| - claudios/code_search_net | |
| library_name: transformers | |
| ## Citation [optional] | |
| <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> | |
| **BibTeX:** | |
| [More Information Needed] | |
| **APA:** | |
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