readme: add initial version

README.md

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+---
+language: fr
+license: mit
+tags:
+  - "historic french"
+---
+# 🤗 + 📚 dbmdz ELECTRA models
+
+In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
+Library open sources French Europeana ELECTRA models 🎉
+
+# French Europeana ELECTRA
+
+We extracted all French texts using the `language` metadata attribute from the Europeana corpus.
+
+The resulting corpus has a size of 63GB and consists of 11,052,528,456 tokens.
+
+Based on the metadata information, texts from the 18th - 20th century are mainly included in the
+training corpus.
+
+Detailed information about the data and pretraining steps can be found in
+[this repository](https://github.com/stefan-it/europeana-bert).
+
+## Model weights
+
+ELECTRA model weights for PyTorch and TensorFlow are available.
+
+* French Europeana ELECTRA (discriminator): `dbmdz/electra-base-french-europeana-cased-discriminator` - [model hub page](https://huggingface.co/dbmdz/electra-base-french-europeana-cased-discriminator/tree/main)
+* French Europeana ELECTRA (generator): `dbmdz/electra-base-french-europeana-cased-generator` - [model hub page](https://huggingface.co/dbmdz/electra-base-french-europeana-cased-generator/tree/main)
+
+## Results
+
+For results on Historic NER, please refer to [this repository](https://github.com/stefan-it/europeana-bert).
+
+## Usage
+
+With Transformers >= 2.3 our French Europeana ELECTRA model can be loaded like:
+
+```python
+from transformers import AutoModel, AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained("dbmdz/electra-base-french-europeana-cased-discriminator")
+model = AutoModel.from_pretrained("dbmdz/electra-base-french-europeana-cased-discriminator")
+```
+
+# Huggingface model hub
+
+All models are available on the [Huggingface model hub](https://huggingface.co/dbmdz).
+
+# Contact (Bugs, Feedback, Contribution and more)
+
+For questions about our ELECTRA models just open an issue
+[here](https://github.com/dbmdz/berts/issues/new) 🤗
+
+# Acknowledgments
+
+Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC).
+Thanks for providing access to the TFRC ❤️
+
+Thanks to the generous support from the [Hugging Face](https://huggingface.co/) team,
+it is possible to download our models from their S3 storage 🤗