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prajjwal1_bert-tiny

prajjwal1 · View on Hugging Face ↗

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language:

  • en

license:

  • mit

tags:

  • BERT
  • MNLI
  • NLI
  • transformer
  • pre-training

The following model is a Pytorch pre-trained model obtained from converting Tensorflow checkpoint found in the official Google BERT repository.

This is one of the smaller pre-trained BERT variants, together with bert-mini bert-small and bert-medium. They were introduced in the study Well-Read Students Learn Better: On the Importance of Pre-training Compact Models (arxiv), and ported to HF for the study Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics (arXiv). These models are supposed to be trained on a downstream task.

If you use the model, please consider citing both the papers:

@misc{bhargava2021generalization,
      title={Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics}, 
      author={Prajjwal Bhargava and Aleksandr Drozd and Anna Rogers},
      year={2021},
      eprint={2110.01518},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@article{DBLP:journals/corr/abs-1908-08962,
  author    = {Iulia Turc and
               Ming{-}Wei Chang and
               Kenton Lee and
               Kristina Toutanova},
  title     = {Well-Read Students Learn Better: The Impact of Student Initialization
               on Knowledge Distillation},
  journal   = {CoRR},
  volume    = {abs/1908.08962},
  year      = {2019},
  url       = {http://arxiv.org/abs/1908.08962},
  eprinttype = {arXiv},
  eprint    = {1908.08962},
  timestamp = {Thu, 29 Aug 2019 16:32:34 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1908-08962.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Config of this model:

Other models to check out:

Original Implementation and more info can be found in this Github repository.

Twitter: @prajjwal_1

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Files & hashes

PathSizesha1sha256
README.md2.5 KB (2,560 B)488d07a361bd823cc0fad0a6661f73ff6debc00055ce99eb2a82b118fe74158365804de22c6909b723135d85dec7f4d9e8518c38
config.json285 B (285 B)234608c922aaf3989d6a772af31711fbbdd62e3acf3179684f7c360dd6185962d480e7d426ceb8fe49f5db7b64bdc15dba0b8798
pytorch_model.bin16.9 MB (17,756,393 B)759bf5640c7dc4acf4b046cb4712ce1dfa358230dab2c2bddcfb48ea430ef63fd76d46d67d704487844d967256a50dd7d7fd0a66
vocab.txt226.1 KB (231,508 B)fb140275c155a9c7c5a3b3e0e77a9e839594a93807eced375cec144d27c900241f3e339478dec958f92fddbc551f295c992038a3

Cite this release

Canonical URL
https://aiseedbank.org/models/prajjwal1_bert-tiny/
Slug
prajjwal1_bert-tiny
Infohash
ee4ee620f27e8c6b3e68038c0e86c68b45c51dbf
License
mit
Signing key fingerprint
85a3b32c3712427b

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Provenance

Upstream repositoryprajjwal1/bert-tiny
Revision (pinned)6f75de8b60a9f8a2fdf7b69cbd86d9e64bcb3837
Fetched at2026-09-04T05:30:46Z
License at fetchmit
Snapshot toolhuggingface · seedbank 0.1.0

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✓ verified · rehash-vs-hf-metadata at 2026-09-04T05:30:47Z

mit17.2 MB (17,990,746 bytes)transformerspytorchBERTMNLINLItransformerpre-trainingendpoints_compatible1 language (en)paper: 1908.08962paper: 2110.01518