Instructions to use codistai/codeBERT-small-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codistai/codeBERT-small-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="codistai/codeBERT-small-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("codistai/codeBERT-small-v2") model = AutoModelForMaskedLM.from_pretrained("codistai/codeBERT-small-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8258be68dda00241f3d193b97a67053617c17b599c47ca3c8fc5eccd6a20b250
- Size of remote file:
- 763 MB
- SHA256:
- 5f88c23524d4799829e3a3ece2b22d4e962446a5a23e980561554ac964e9eabe
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