Instructions to use argv947059/example-based-ner-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use argv947059/example-based-ner-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="argv947059/example-based-ner-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("argv947059/example-based-ner-bert") model = AutoModel.from_pretrained("argv947059/example-based-ner-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 300 Bytes
aff487d | 1 | {"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "name_or_path": "bert-base-uncased"} |