Token Classification
Transformers
Safetensors
English
bert
finance
terminology
term-extraction
english
ner
Instructions to use owen4512/bert-base-cased-finance-term-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use owen4512/bert-base-cased-finance-term-extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="owen4512/bert-base-cased-finance-term-extractor")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("owen4512/bert-base-cased-finance-term-extractor") model = AutoModelForTokenClassification.from_pretrained("owen4512/bert-base-cased-finance-term-extractor") - Notebooks
- Google Colab
- Kaggle
File size: 322 Bytes
c3358bb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"backend": "tokenizers",
"cls_token": "[CLS]",
"do_lower_case": false,
"is_local": true,
"mask_token": "[MASK]",
"model_max_length": 512,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
"unk_token": "[UNK]"
}
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