Instructions to use aieng-lab/bert-base-cased_comment-type-java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aieng-lab/bert-base-cased_comment-type-java with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aieng-lab/bert-base-cased_comment-type-java")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aieng-lab/bert-base-cased_comment-type-java") model = AutoModelForSequenceClassification.from_pretrained("aieng-lab/bert-base-cased_comment-type-java") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ae2d74f14c39bd1b66a8a5d976ee523fbbb9153d66f9e636c8a49ca9ef3fd2f
- Size of remote file:
- 217 MB
- SHA256:
- c641e39b0d8c5995411b476f4dcb7f3a982b3c1d74ba4f8baeb7a3aae5481351
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