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[model_cards]: 🇹🇷 Add new ELECTRA small and base models for Turkish (#4318)
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Stefan Schweter
GitHub
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language: turkish
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license: mit
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---
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# 🤗 + 📚 dbmdz Turkish ELECTRA model
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In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
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Library open sources a cased ELECTRA base model for Turkish 🎉
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# Turkish ELECTRA model
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We release a base ELEC**TR**A model for Turkish, that was trained on the same data as *BERTurk*.
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> ELECTRA is a new method for self-supervised language representation learning. It can be used to
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> pre-train transformer networks using relatively little compute. ELECTRA models are trained to
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> distinguish "real" input tokens vs "fake" input tokens generated by another neural network, similar to
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> the discriminator of a GAN.
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More details about ELECTRA can be found in the [ICLR paper](https://openreview.net/forum?id=r1xMH1BtvB)
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or in the [official ELECTRA repository](https://github.com/google-research/electra) on GitHub.
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## Stats
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The current version of the model is trained on a filtered and sentence
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segmented version of the Turkish [OSCAR corpus](https://traces1.inria.fr/oscar/),
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a recent Wikipedia dump, various [OPUS corpora](http://opus.nlpl.eu/) and a
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special corpus provided by [Kemal Oflazer](http://www.andrew.cmu.edu/user/ko/).
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The final training corpus has a size of 35GB and 44,04,976,662 tokens.
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Thanks to Google's TensorFlow Research Cloud (TFRC) we could train a cased model
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on a TPU v3-8 for 1M steps.
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## Model weights
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[Transformers](https://github.com/huggingface/transformers)
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compatible weights for both PyTorch and TensorFlow are available.
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| Model | Downloads
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| ------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------
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| `dbmdz/electra-base-turkish-cased-discriminator` | [`config.json`](https://cdn.huggingface.co/dbmdz/electra-base-turkish-cased-discriminator/config.json) • [`pytorch_model.bin`](https://cdn.huggingface.co/dbmdz/electra-base-turkish-cased-discriminator/pytorch_model.bin) • [`vocab.txt`](https://cdn.huggingface.co/dbmdz/electra-base-turkish-cased-discriminator/vocab.txt)
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## Usage
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With Transformers >= 2.8 our ELECTRA base cased model can be loaded like:
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```python
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from transformers import AutoModelWithLMHead, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("dbmdz/electra-base-turkish-cased-discriminator")
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model = AutoModelWithLMHead.from_pretrained("dbmdz/electra-base-turkish-cased-discriminator")
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```
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## Results
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For results on PoS tagging or NER tasks, please refer to
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[this repository](https://github.com/stefan-it/turkish-bert/electra).
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# Huggingface model hub
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All models are available on the [Huggingface model hub](https://huggingface.co/dbmdz).
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# Contact (Bugs, Feedback, Contribution and more)
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For questions about our ELECTRA models just open an issue
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[here](https://github.com/dbmdz/berts/issues/new) 🤗
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# Acknowledgments
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Thanks to [Kemal Oflazer](http://www.andrew.cmu.edu/user/ko/) for providing us
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additional large corpora for Turkish. Many thanks to Reyyan Yeniterzi for providing
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us the Turkish NER dataset for evaluation.
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Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC).
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Thanks for providing access to the TFRC ❤️
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Thanks to the generous support from the [Hugging Face](https://huggingface.co/) team,
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it is possible to download both cased and uncased models from their S3 storage 🤗
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@ -0,0 +1,79 @@
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---
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language: turkish
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license: mit
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---
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# 🤗 + 📚 dbmdz Turkish ELECTRA model
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In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
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Library open sources a cased ELECTRA small model for Turkish 🎉
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# Turkish ELECTRA model
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We release a small ELEC**TR**A model for Turkish, that was trained on the same data as *BERTurk*.
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|
|
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> ELECTRA is a new method for self-supervised language representation learning. It can be used to
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> pre-train transformer networks using relatively little compute. ELECTRA models are trained to
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> distinguish "real" input tokens vs "fake" input tokens generated by another neural network, similar to
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> the discriminator of a GAN.
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More details about ELECTRA can be found in the [ICLR paper](https://openreview.net/forum?id=r1xMH1BtvB)
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or in the [official ELECTRA repository](https://github.com/google-research/electra) on GitHub.
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## Stats
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The current version of the model is trained on a filtered and sentence
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segmented version of the Turkish [OSCAR corpus](https://traces1.inria.fr/oscar/),
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a recent Wikipedia dump, various [OPUS corpora](http://opus.nlpl.eu/) and a
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special corpus provided by [Kemal Oflazer](http://www.andrew.cmu.edu/user/ko/).
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The final training corpus has a size of 35GB and 44,04,976,662 tokens.
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Thanks to Google's TensorFlow Research Cloud (TFRC) we could train a cased model
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on a TPU v3-8 for 1M steps.
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## Model weights
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[Transformers](https://github.com/huggingface/transformers)
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compatible weights for both PyTorch and TensorFlow are available.
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| Model | Downloads
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| ------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------
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| `dbmdz/electra-small-turkish-cased-discriminator` | [`config.json`](https://cdn.huggingface.co/dbmdz/electra-small-turkish-cased-discriminator/config.json) • [`pytorch_model.bin`](https://cdn.huggingface.co/dbmdz/electra-small-turkish-cased-discriminator/pytorch_model.bin) • [`vocab.txt`](https://cdn.huggingface.co/dbmdz/electra-small-turkish-cased-discriminator/vocab.txt)
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## Usage
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With Transformers >= 2.8 our ELECTRA small cased model can be loaded like:
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```python
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from transformers import AutoModelWithLMHead, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("dbmdz/electra-small-turkish-cased-discriminator")
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model = AutoModelWithLMHead.from_pretrained("dbmdz/electra-small-turkish-cased-discriminator")
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```
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## Results
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For results on PoS tagging or NER tasks, please refer to
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[this repository](https://github.com/stefan-it/turkish-bert/electra).
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# Huggingface model hub
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All models are available on the [Huggingface model hub](https://huggingface.co/dbmdz).
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# Contact (Bugs, Feedback, Contribution and more)
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For questions about our ELECTRA models just open an issue
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[here](https://github.com/dbmdz/berts/issues/new) 🤗
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# Acknowledgments
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Thanks to [Kemal Oflazer](http://www.andrew.cmu.edu/user/ko/) for providing us
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additional large corpora for Turkish. Many thanks to Reyyan Yeniterzi for providing
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us the Turkish NER dataset for evaluation.
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Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC).
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Thanks for providing access to the TFRC ❤️
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|
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Thanks to the generous support from the [Hugging Face](https://huggingface.co/) team,
|
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it is possible to download both cased and uncased models from their S3 storage 🤗
|
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