# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("christofid/dapscibert")
model = AutoModelForMaskedLM.from_pretrained("christofid/dapscibert")Quick Links
dapSciBERT
DapSciBERT is a BERT-like model trained based on the domain adaptive pretraining method (Gururangan et al.) for the patent domain. Allenai/scibert_scivocab_uncased is used as base for the training. The training dataset used consists of a corpus of 10,000,000 patent abstracts that have been filed between 1998-2020 in US and European patent offices as well as the World Intellectual Property Organization.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="christofid/dapscibert")