fathyshalab / massive_play-roberta-large-v1-4-71

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Total runs: 6
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Model's Last Updated: February 10 2023
text-classification

Introduction of massive_play-roberta-large-v1-4-71

Model Details of massive_play-roberta-large-v1-4-71

fathyshalab/massive_play-roberta-large-v1-4-71

This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:

  1. Fine-tuning a Sentence Transformer with contrastive learning.
  2. Training a classification head with features from the fine-tuned Sentence Transformer.
Usage

To use this model for inference, first install the SetFit library:

python -m pip install setfit

You can then run inference as follows:

from setfit import SetFitModel

# Download from Hub and run inference
model = SetFitModel.from_pretrained("fathyshalab/massive_play-roberta-large-v1-4-71")
# Run inference
preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"])
BibTeX entry and citation info
@article{https://doi.org/10.48550/arxiv.2209.11055,
doi = {10.48550/ARXIV.2209.11055},
url = {https://arxiv.org/abs/2209.11055},
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Efficient Few-Shot Learning Without Prompts},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution 4.0 International}
}

Runs of fathyshalab massive_play-roberta-large-v1-4-71 on huggingface.co

6
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0
24-hour runs
-1
3-day runs
-3
7-day runs
-2
30-day runs

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