README.md

metadata

base_model:
  - rrivera1849/LUAR-CRUD
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
  - sentence-transformers
  - sentence-similarity
  - LUAR
license: apache-2.0
language:
  - en

SentenceTransformer version of rrivera1849/LUAR-MUD

All credits go to (Rivera-Soto et al. 2021)

---

Author Style Representations using LUAR.

The LUAR training and evaluation repository can be found here.

This model was trained on a subsample of the Pushshift Reddit Dataset (5 million users) for comments published between January 2015 and October 2019 by authors publishing at least 100 comments during that period.

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("gabrielloiseau/LUAR-CRUD-sentence-transformers")
# Run inference
sentences = [
    'The weather is lovely today.',
    "It's so sunny outside!",
    'He drove to the stadium.',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 512]

Citation

If you find this model helpful, feel free to cite:

@inproceedings{uar-emnlp2021,
  author    = {Rafael A. Rivera Soto and Olivia Miano and Juanita Ordonez and Barry Chen and Aleem Khan and Marcus Bishop and Nicholas Andrews},
  title     = {Learning Universal Authorship Representations},
  booktitle = {EMNLP},
  year      = {2021},
}

License

LUAR is distributed under the terms of the Apache License (Version 2.0).

All new contributions must be made under the Apache-2.0 licenses.