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---
license: llama2
datasets:
- hlab/SocialiteInstructions
language:
- en
library_name: transformers
---
# Socialite-Llama Model Card
## Model Details
**Model Type** : Socialite-Llama is an open-source, instruction tuned Llama2 7B on [SocialiteInstructions](https://huggingface.co./datasets/hlab/SocialiteInstructions). On a suite of 20 social science tasks, Socialite-Llama improves upon the performance of Llama as well as matches or improves upon the performance of a state-of-the-art, multi-task finetuned model on a majority of them. Further, Socialite-Llama also leads to improvement on 5 out of 6 related social tasks as compared to Llama, suggesting instruction tuning can lead to generalized social understanding.
**Model date**: Socialite-Llama was trained on October, 2023.
**Paper Details**: [https://arxiv.org/abs/2402.01980]
**Github**: [https://github.com/humanlab/socialitellama]
## License
Llama 2 is licensed under the LLAMA 2 Community License, Copyright (c) Meta Platforms, Inc. All Rights Reserved.
## Training Dataset
* 108k datapoints of <Instruction, Input, Output> triplets
* 20 diverse datasets covering a broad range of social scientific tasks
## Evaluation Dataset
* 20 tasks which the model has seen during training
* 6 related social tasks which the model has not seen during its training
## Intended Use
The primary intended use of Socialite Llama is research on Computation Social Science and Cultural Analytics.
## Citation Information
```
@inproceedings{
dey-etal-2024-socialite,
title={{SOCIALITE}-{LLAMA}: An Instruction-Tuned Model for Social Scientific Tasks},
author={Dey, Gourab and V Ganesan, Adithya and Lal, Yash Kumar and Shah, Manal and Sinha, Shreyashee and Matero, Matthew and Giorgi, Salvatore and Kulkarni, Vivek and Schwartz, H. Andrew},
address = "St. Julian’s, Malta",
booktitle={18th Conference of the European Chapter of the Association for Computational Linguistics},
year={2024},
publisher = {Association for Computational Linguistics}
}
```
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