readme: add initial version with awesome logo from Merve!

README.md

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+---
+language: tr
+license: mit
+datasets:
+- allenai/c4
+widget:
+- text: "Dünyanın en eski şehirlerinden biri olan [MASK]"
+---
+
+# 🇹🇷 Turkish ELECTRA model
+
+<p align="center">
+  <img alt="Logo provided by Merve Noyan" title="Awesome logo from Merve Noyan" src="https://raw.githubusercontent.com/stefan-it/turkish-bert/updates/merve_logo.png">
+</p>
+
+[![DOI](https://zenodo.org/badge/237817454.svg)](https://zenodo.org/badge/latestdoi/237817454)
+
+We present community-driven BERT, DistilBERT, ELECTRA and ConvBERT models for Turkish 🎉
+
+Some datasets used for pretraining and evaluation are contributed from the
+awesome Turkish NLP community, as well as the decision for the BERT model name: BERTurk.
+
+Logo is provided by [Merve Noyan](https://twitter.com/mervenoyann).
+
+# Stats
+
+We've also trained an ELECTRA (cased) model on the recently released Turkish part of the
+[multiligual C4 (mC4) corpus](https://github.com/allenai/allennlp/discussions/5265) from the AI2 team.
+
+After filtering documents with a broken encoding, the training corpus has a size of 242GB resulting
+in 31,240,963,926 tokens.
+
+We used the original 32k vocab (instead of creating a new one).
+
+# mC4 ELECTRA
+
+In addition to the ELEC**TR**A base model, we also trained an ELECTRA model on the Turkish part of the mC4 corpus. We use a
+sequence length of 512 over the full training time and train the model for 1M steps on a v3-32 TPU.
+
+# Model usage
+
+All trained models can be used from the [DBMDZ](https://github.com/dbmdz) Hugging Face [model hub page](https://huggingface.co/dbmdz)
+using their model name.
+
+Example usage with 🤗/Transformers:
+
+```python
+tokenizer = AutoTokenizer.from_pretrained("dbmdz/electra-small-turkish-mc4-cased-generator")
+
+model = AutoModel.from_pretrained("dbmdz/electra-small-turkish-mc4-cased-generator")
+```
+
+# Citation
+
+You can use the following BibTeX entry for citation:
+
+```bibtex
+@software{stefan_schweter_2020_3770924,
+  author       = {Stefan Schweter},
+  title        = {BERTurk - BERT models for Turkish},
+  month        = apr,
+  year         = 2020,
+  publisher    = {Zenodo},
+  version      = {1.0.0},
+  doi          = {10.5281/zenodo.3770924},
+  url          = {https://doi.org/10.5281/zenodo.3770924}
+}
+```
+
+# Acknowledgments
+
+Thanks to [Kemal Oflazer](http://www.andrew.cmu.edu/user/ko/) for providing us
+additional large corpora for Turkish. Many thanks to Reyyan Yeniterzi for providing
+us the Turkish NER dataset for evaluation.
+
+We would like to thank [Merve Noyan](https://twitter.com/mervenoyann) for the
+awesome logo!
+
+Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC).
+Thanks for providing access to the TFRC ❤️