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 No longer maintained; retained for reproducibility.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/bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("fill-mask", model="binwang/bert-base-uncased") # Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("binwang/bert-base-uncased")
model = AutoModelForMaskedLM.from_pretrained("binwang/bert-base-uncased", device_map="auto")No longer actively maintained. Retained for reproducibility of the original work.
This repository hosts the original 12-layer BERT checkpoint used in the SBERT-WK experiments. It is a supporting checkpoint for the sentence embedding method.
For the paper, original software environment, and reproduction instructions, see SBERT-WK: A Sentence Embedding Method by Dissecting BERT-based Word Models.