Instructions to use fasterinnerlooper/codeBERTa-csharp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fasterinnerlooper/codeBERTa-csharp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fasterinnerlooper/codeBERTa-csharp")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fasterinnerlooper/codeBERTa-csharp") model = AutoModelForMaskedLM.from_pretrained("fasterinnerlooper/codeBERTa-csharp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38c413a88378b2ea64ef5b74f7e98226c049cb2a5c1655ee575155fa9561b968
- Size of remote file:
- 334 MB
- SHA256:
- d5ccfff5f29e4f915cb687dfc6376be04a5e881299d8697e48b84061baf50cfe
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