Instructions to use aieng-lab/t5-large_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-large_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-large_comment-type-java")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aieng-lab/t5-large_comment-type-java") model = AutoModelForSequenceClassification.from_pretrained("aieng-lab/t5-large_comment-type-java", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaa3bad1ab453fcf0ab31fdd47324e4c03986692c47c2d01cf009594663c767b
- Size of remote file:
- 1.48 GB
- SHA256:
- 86002cfa86308ac1245a5155a0706ed99288bc218cd8fd127a7a755ca6a01e8c
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