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:
- 8771e177b0ad7086e4e10e583c0ba1491d08385bf913303d4411faabce6db9d0
- Size of remote file:
- 438 MB
- SHA256:
- 89e3f9998e9b11352b15cb21c773e074decc7387a0aad34b62ae74d2d688548d
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