Instructions to use giganticode/bert-base-code_comments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use giganticode/bert-base-code_comments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="giganticode/bert-base-code_comments")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("giganticode/bert-base-code_comments") model = AutoModelForMaskedLM.from_pretrained("giganticode/bert-base-code_comments") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44c971a8183dd0f107b4282c388f112d0f159922badd04ffab3cf28038e6f062
- Size of remote file:
- 438 MB
- SHA256:
- 6c663b277e26e04a9833b166c8c079da27c35ff8814ff40cec151259d414d77c
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