Instructions to use giganticode/bert-base-StackOverflow-comments_2M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use giganticode/bert-base-StackOverflow-comments_2M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="giganticode/bert-base-StackOverflow-comments_2M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("giganticode/bert-base-StackOverflow-comments_2M") model = AutoModelForMaskedLM.from_pretrained("giganticode/bert-base-StackOverflow-comments_2M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8bdf652345893f0ff5013b0392f0b8869cb1524874e995f148b0faba4950e22
- Size of remote file:
- 438 MB
- SHA256:
- 260af741330682bde4c173983cf7ae8f5d3cc1899b20640026932a4eded72cab
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