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:
- 4fa536af692e288450aa88554e5adf43902fc555c5516b279bd1008b5f2d2352
- Size of remote file:
- 4.54 kB
- SHA256:
- 047c6b6bfba1c0612bb4b109d57ae5fa34fb052b1e7bbcb6159940cd0f16a279
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