Instructions to use binwang/RSE-BERT-large-USEB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binwang/RSE-BERT-large-USEB with Transformers:
# Load model directly from transformers import AutoTokenizer, BertForRSE tokenizer = AutoTokenizer.from_pretrained("binwang/RSE-BERT-large-USEB") model = BertForRSE.from_pretrained("binwang/RSE-BERT-large-USEB") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
The RSE-BERT-large-USEB is trained with 6 relations including:
- entailment
- duplicate_question
- paraphrase
- same_caption
- qa_entailment
- same_sent
The BERT-large-uncased model is used as initialization.
It can be used ideally for USEB datasets.
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