How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("fill-mask", model="viswavi/datafinder-scibert-nl-queries")
# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("viswavi/datafinder-scibert-nl-queries")
model = AutoModel.from_pretrained("viswavi/datafinder-scibert-nl-queries")
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This is a version of the SciBERT encoder trained for the purpose of retrieving datasets by textual description given a natural language query.

If useful, please cite

@inproceedings{viswanathan23acl,
    title = {DataFinder: Scientific Dataset Recommendation from Natural Language Descriptions},
    author = {Vijay Viswanathan and Luyu Gao and Tongshuang Wu and Pengfei Liu and Graham Neubig},
    booktitle = {Annual Conference of the Association for Computational Linguistics (ACL)},
    address = {Toronto, Canada},
    month = {July},
    url = {https://arxiv.org/abs/2305.16636},
    year = {2023}
}
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Paper for viswavi/datafinder-scibert-nl-queries