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") - Notebooks
- Google Colab
- Kaggle
File size: 345 Bytes
7ee6f49 1e21810 c989ead 0b4cebe 1e21810 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ---
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:**
[More Information Needed] |