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README.md

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 ## Introduction
 
-This model is a model that was fine-tuned from [Jean-Baptiste/camembert-ner](https://huggingface.co/nlpso/Jean-Baptiste/camembert-ner) for **nested NER task** on a nested NER Paris trade directories dataset.
+This model is a model that was fine-tuned from [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) for **nested NER task** on a nested NER Paris trade directories dataset.
 
 ## Dataset
 
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 ## Experiment parameter
 
-* Pretrained-model : [Jean-Baptiste/camembert-ner](https://huggingface.co/nlpso/Jean-Baptiste/camembert-ner)
+* Pretrained-model : [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner)
 * Dataset : ground-truth
 * Tagging format : IO
 * Recognised entities : level 2
 
 ## Load model from the Hugging Face
 
-**Warning** : this model only recognises level-2 entities of dataset. It has to be used with [m1_ind_layers_ref_cmbert_io_level_1](https://huggingface.co/nlpso/m1_ind_layers_ref_cmbert_io_level_1) to recognise nested entities level-1.
+**Warning 1 ** : this model only recognises level-2 entities of dataset. It has to be used with [m1_ind_layers_ref_cmbert_io_level_1](https://huggingface.co/nlpso/m1_ind_layers_ref_cmbert_io_level_1) to recognise nested entities level-1.
 
 ```python
 from transformers import AutoTokenizer, AutoModelForTokenClassification
 
-tokenizer = AutoTokenizer.from_pretrained("m1_ind_layers_ref_cmbert_io_level_2")
-model = AutoModelForTokenClassification.from_pretrained("m1_ind_layers_ref_cmbert_io_level_2")
+tokenizer = AutoTokenizer.from_pretrained(nlpso/"m1_ind_layers_ref_cmbert_io_level_2")
+model = AutoModelForTokenClassification.from_pretrained(nlpso/"m1_ind_layers_ref_cmbert_io_level_2")