Token Classification
SpanMarker
PyTorch
TensorBoard
Safetensors
Tagalog
ner
named-entity-recognition
generated_from_span_marker_trainer
Eval Results (legacy)
Instructions to use tomaarsen/span-marker-mbert-base-tlunified with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use tomaarsen/span-marker-mbert-base-tlunified with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-mbert-base-tlunified") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": true, | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "entity_max_length": 8, | |
| "marker_max_length": 128, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 256, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |