Instructions to use giganticode/bert-base-StackOverflow-comments_1M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use giganticode/bert-base-StackOverflow-comments_1M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="giganticode/bert-base-StackOverflow-comments_1M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("giganticode/bert-base-StackOverflow-comments_1M") model = AutoModelForMaskedLM.from_pretrained("giganticode/bert-base-StackOverflow-comments_1M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54682bc96770ce90a7116d15d8acf2264354afc3f7d609348081e79fe4ab83eb
- Size of remote file:
- 438 MB
- SHA256:
- 08ef91983ef93782e68105ef73b230d491fd6d14a9d7f45910836e9386c99949
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