# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("mukund/privbert")
model = AutoModelForMaskedLM.from_pretrained("mukund/privbert")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
PrivBERT
PrivBERT is a privacy policy language model. We pre-trained PrivBERT on ~1 million privacy policies starting with the pretrained Roberta model. The data is available at https://privaseer.ist.psu.edu/data
Usage
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("mukund/privbert")
model = AutoModel.from_pretrained("mukund/privbert")
License
If you use this dataset in research, you must cite the below paper.
Mukund Srinath, Shomir Wilson and C. Lee Giles. Privacy at Scale: Introducing the PrivaSeer Corpus of Web Privacy Policies. In Proc. ACL 2021.
For research, teaching, and scholarship purposes, the model is available under a CC BY-NC-SA license. Please contact us for any requests regarding commercial use.
- Downloads last month
- 856
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mukund/privbert")