Research Archive
Collection
Historical artifacts from SBERT-WK, RSE, InstructDS, and earlier research. No longer maintained; retained for reproducibility. โข 32 items โข Updated
How to use binwang/RSE-BERT-base-Transfer with Transformers:
# Load model directly
from transformers import AutoTokenizer, BertForRSE
tokenizer = AutoTokenizer.from_pretrained("binwang/RSE-BERT-base-Transfer")
model = BertForRSE.from_pretrained("binwang/RSE-BERT-base-Transfer", device_map="auto")No longer actively maintained. Retained for reproducibility of the original work.
This repository contains one variant of the RSE research models. The repository name identifies the backbone (BERT or RoBERTa), model size (base or large), and experiment variant (STS, USEB, Transfer, or 10-relations). Refer to the original description below for this checkpoint's configuration.
The RSE-BERT-base-Transfer is trained with 2 relations including:
The BERT-base-uncased model is used as initialization.
It can be used ideally for Transfer datasets - (Downstream Tasks) .