Update README.md

README.md

@@ -1,3 +1,32 @@
 ---
+language: fr
+pipeline_tag: fill-mask
 license: cc-by-sa-4.0
+tags:
+- legal
+widget:
+- text: "Chaque commune de la Région peut adopter un <mask> communal de développement, applicable à l'ensemble de son territoire."
 ---
+
+# Legal-CamemBERT
+
+* Legal-DistilCamemBERT is a [DistilCamemBERT](https://huggingface.co/cmarkea/distilcamembert-base)-based model further pre-trained on [23,000+ statutory articles](https://huggingface.co/datasets/maastrichtlawtech/bsard) from the Belgian legislation.
+* We chose the following training set-up: 50k training steps (200 epochs) with batches of 32 sequences of length 512 with an initial learning rate of 5e-5.
+* Training was performed on one Tesla V100 GPU with 32 GB using the [code](https://github.com/huggingface/transformers/blob/main/examples/pytorch/language-modeling/run_mlm.py) provided by Hugging Face.
+
+---
+
+### Load Pretrained Model
+
+```python
+from transformers import AutoTokenizer, AutoModel
+
+tokenizer = AutoTokenizer.from_pretrained("maastrichtlawtech/legal-distilcamembert")
+model = AutoModel.from_pretrained("maastrichtlawtech/legal-distilcamembert")
+```
+
+### About Us
+
+The [Maastricht Law & Tech Lab](https://www.maastrichtuniversity.nl/about-um/faculties/law/research/law-and-tech-lab) develops algorithms, models, and systems that allow computers to process natural language texts from the legal domain.
+
+Author: [Antoine Louis](https://antoinelouis.co) on behalf of the [Maastricht Law & Tech Lab](https://www.maastrichtuniversity.nl/about-um/faculties/law/research/law-and-tech-lab).