Instructions to use bltlab/queryner-augmented-data-bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bltlab/queryner-augmented-data-bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bltlab/queryner-augmented-data-bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bltlab/queryner-augmented-data-bert-base-uncased") model = AutoModelForTokenClassification.from_pretrained("bltlab/queryner-augmented-data-bert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 451 Bytes
8d6048f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"add_prefix_space": false,
"clean_up_tokenization_spaces": true,
"cls_token": "[CLS]",
"do_lower_case": true,
"mask_token": "[MASK]",
"max_length": 512,
"model_max_length": 512,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"stride": 0,
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
"truncation_side": "right",
"truncation_strategy": "longest_first",
"unk_token": "[UNK]"
}
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