Instructions to use giganticode/bert-large-StackOverflow-comments_1M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use giganticode/bert-large-StackOverflow-comments_1M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="giganticode/bert-large-StackOverflow-comments_1M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("giganticode/bert-large-StackOverflow-comments_1M") model = AutoModelForMaskedLM.from_pretrained("giganticode/bert-large-StackOverflow-comments_1M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 187a0be2e513abbb58e288789ce589dd32d47a363d072ab392d5068930ca08b6
- Size of remote file:
- 1.34 GB
- SHA256:
- d22d6f6f79c27d8e9eb600e9735c5ea4e80efb4a99f92e474292697eb2a9e0aa
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