Instructions to use arnolfokam/mbert-base-uncased-ner-kin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arnolfokam/mbert-base-uncased-ner-kin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arnolfokam/mbert-base-uncased-ner-kin")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("arnolfokam/mbert-base-uncased-ner-kin") model = AutoModelForTokenClassification.from_pretrained("arnolfokam/mbert-base-uncased-ner-kin") - Notebooks
- Google Colab
- Kaggle
| {"do_lower_case": false, "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": "Davlan/bert-base-multilingual-cased-ner-hrl", "special_tokens_map_file": "/root/.cache/huggingface/transformers/fc3a79016f096a135e80719eb09df8a9e23a8bafc34c1e8a24a2eab2318e7fc3.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"} |