Token Classification
Transformers
Safetensors
French
bert
newsagency
ner
historical
impresso
multilingual
Instructions to use impresso-project/ner-newsagency-bert-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use impresso-project/ner-newsagency-bert-fr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="impresso-project/ner-newsagency-bert-fr")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("impresso-project/ner-newsagency-bert-fr") model = AutoModelForTokenClassification.from_pretrained("impresso-project/ner-newsagency-bert-fr") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer.json +0 -0
- tokenizer_config.json +8 -5
- vocab.txt +0 -0
tokenizer.json
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tokenizer_config.json
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"single_word": false,
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"special": true
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},
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"single_word": false,
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"special": true
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},
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"single_word": false,
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"special": true
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},
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"single_word": false,
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"special": true
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},
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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},
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents":
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"single_word": false,
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"special": true
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"3": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"single_word": false,
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"special": true
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"4": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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},
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"max_len": 512,
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"model_max_length": 512,
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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": false,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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vocab.txt
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