Instructions to use aieng-lab/t5-small_comment-type-java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aieng-lab/t5-small_comment-type-java with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aieng-lab/t5-small_comment-type-java")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aieng-lab/t5-small_comment-type-java") model = AutoModelForSequenceClassification.from_pretrained("aieng-lab/t5-small_comment-type-java", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57b4fb071dbb769cee3d0ebc8d7be8d3c2ebdd39ac61c55cac85eded06646507
- Size of remote file:
- 122 MB
- SHA256:
- 0485af815187e87efd5b257c12ba21e0d390fff7d0b546d68c335c40449ae55e
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