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:
- 09f698b63c1085e118230906f1040bde0ea08dc605221ddc978722822fb0dc9f
- Size of remote file:
- 438 MB
- SHA256:
- e60df9448f7ca0b22c5a442a4199922b86c2a98b42abc28950cb21a2d6776074
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