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  ## Introduction
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- This model is a fine-tuned verion 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.
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  ## Dataset
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  ## Experiment parameter
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- * Pretrained-model : [Jean-Baptiste/camembert-ner](https://huggingface.co/nlpso/Jean-Baptiste/camembert-ner)
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  * Dataset : ground-truth
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  * Tagging format : IO
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  * Recognised entities : 'All'
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  ```python
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  from transformers import AutoTokenizer, AutoModelForTokenClassification
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- tokenizer = AutoTokenizer.from_pretrained("m2_joint_label_ref_ptrn_cmbert_io")
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- model = AutoModelForTokenClassification.from_pretrained("m2_joint_label_ref_ptrn_cmbert_io")
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  ## Introduction
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+ This model is a fine-tuned verion from [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) for **nested NER task** on a nested NER Paris trade directories dataset.
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  ## Dataset
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  ## Experiment parameter
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+ * Pretrained-model : [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner)
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  * Dataset : ground-truth
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  * Tagging format : IO
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  * Recognised entities : 'All'
 
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  ```python
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  from transformers import AutoTokenizer, AutoModelForTokenClassification
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+ tokenizer = AutoTokenizer.from_pretrained("nlpso/m2_joint_label_ref_ptrn_cmbert_io")
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+ model = AutoModelForTokenClassification.from_pretrained("nlpso/m2_joint_label_ref_ptrn_cmbert_io")
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