Instructions to use aieng-lab/t5-base_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-base_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-base_comment-type-java")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aieng-lab/t5-base_comment-type-java") model = AutoModelForSequenceClassification.from_pretrained("aieng-lab/t5-base_comment-type-java", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3aa8724ce3a7c64f675943dbdd16c14d6f4cbf047665c558fa3f5dbf184b61c8
- Size of remote file:
- 447 MB
- SHA256:
- 1d049974742aa83abe070da8ca483e3e443797746a656ff6fb6fc8e2cc412207
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