Instructions to use maia2000/ner-camembert-camembert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maia2000/ner-camembert-camembert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="maia2000/ner-camembert-camembert-large")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("maia2000/ner-camembert-camembert-large") model = AutoModelForTokenClassification.from_pretrained("maia2000/ner-camembert-camembert-large") - Notebooks
- Google Colab
- Kaggle
Upload label_mapping.json with huggingface_hub
Browse files- label_mapping.json +32 -0
label_mapping.json
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{
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"label2id": {
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"B-ARR": 0,
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"B-DEP": 1,
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"B-MISC": 2,
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"B-PER": 3,
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"B-TEMP": 4,
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"B-TRANSPORT": 5,
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"I-ARR": 6,
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"I-DEP": 7,
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"I-MISC": 8,
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"I-PER": 9,
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"I-TEMP": 10,
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"I-TRANSPORT": 11,
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"O": 12
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},
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"id2label": {
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"0": "B-ARR",
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"1": "B-DEP",
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"2": "B-MISC",
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"3": "B-PER",
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"4": "B-TEMP",
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"5": "B-TRANSPORT",
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"6": "I-ARR",
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"7": "I-DEP",
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"8": "I-MISC",
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"9": "I-PER",
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"10": "I-TEMP",
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"11": "I-TRANSPORT",
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"12": "O"
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}
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}
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