prajjwal1 / bert-medium

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Total runs: 111.1K
24-hour runs: 9.1K
7-day runs: 43.9K
30-day runs: -153.8K
Model's Last Updated: October 28 2021

Introduction of bert-medium

Model Details of bert-medium

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-tiny , bert-mini and bert-small . 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

Runs of prajjwal1 bert-medium on huggingface.co

111.1K
Total runs
9.1K
24-hour runs
24.5K
3-day runs
43.9K
7-day runs
-153.8K
30-day runs

More Information About bert-medium huggingface.co Model

More bert-medium license Visit here:

https://choosealicense.com/licenses/mit

bert-medium huggingface.co

bert-medium huggingface.co is an AI model on huggingface.co that provides bert-medium's model effect (), which can be used instantly with this prajjwal1 bert-medium model. huggingface.co supports a free trial of the bert-medium model, and also provides paid use of the bert-medium. Support call bert-medium model through api, including Node.js, Python, http.

prajjwal1 bert-medium online free

bert-medium huggingface.co is an online trial and call api platform, which integrates bert-medium's modeling effects, including api services, and provides a free online trial of bert-medium, you can try bert-medium online for free by clicking the link below.

prajjwal1 bert-medium online free url in huggingface.co:

https://huggingface.co/prajjwal1/bert-medium

bert-medium install

bert-medium is an open source model from GitHub that offers a free installation service, and any user can find bert-medium on GitHub to install. At the same time, huggingface.co provides the effect of bert-medium install, users can directly use bert-medium installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

bert-medium install url in huggingface.co:

https://huggingface.co/prajjwal1/bert-medium

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bert-medium huggingface.co Url

Provider of bert-medium huggingface.co

prajjwal1
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