antoinelouis
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README.md
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développement, applicable à l'ensemble de son territoire.
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# Legal-CamemBERT
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* Legal-CamemBERT is a [CamemBERT](https://huggingface.co/camembert-base)
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* 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.
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* 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.
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("maastrichtlawtech/legal-camembert")
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model = AutoModel.from_pretrained("maastrichtlawtech/legal-camembert")
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```
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### About Us
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développement, applicable à l'ensemble de son territoire.
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# Legal-CamemBERT-Base
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* Legal-CamemBERT-Base is a [CamemBERT-Base](https://huggingface.co/camembert-base) model further pre-trained on [23,000+ legislative articles](https://huggingface.co/datasets/maastrichtlawtech/bsard) from the Belgian legislation.
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* 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.
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* 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.
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("maastrichtlawtech/legal-camembert-base")
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model = AutoModel.from_pretrained("maastrichtlawtech/legal-camembert-base")
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```
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### About Us
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