Token Classification
Transformers
Safetensors
Vietnamese
roberta
ner
vietnamese
address-parsing
phobert
Eval Results (legacy)
Instructions to use open-thienhang-com/bert_all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use open-thienhang-com/bert_all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="open-thienhang-com/bert_all")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("open-thienhang-com/bert_all") model = AutoModelForTokenClassification.from_pretrained("open-thienhang-com/bert_all") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "RobertaForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": 0.1, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "<PAD>", | |
| "1": "B-CITY", | |
| "2": "B-DISTRICT", | |
| "3": "B-HOUSE_NUMBER", | |
| "4": "B-PLACE_NAME", | |
| "5": "B-STREET", | |
| "6": "B-WARD", | |
| "7": "I-CITY", | |
| "8": "I-DISTRICT", | |
| "9": "I-HOUSE_NUMBER", | |
| "10": "I-PLACE_NAME", | |
| "11": "I-STREET", | |
| "12": "I-WARD", | |
| "13": "O" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "<PAD>": 0, | |
| "B-CITY": 1, | |
| "B-DISTRICT": 2, | |
| "B-HOUSE_NUMBER": 3, | |
| "B-PLACE_NAME": 4, | |
| "B-STREET": 5, | |
| "B-WARD": 6, | |
| "I-CITY": 7, | |
| "I-DISTRICT": 8, | |
| "I-HOUSE_NUMBER": 9, | |
| "I-PLACE_NAME": 10, | |
| "I-STREET": 11, | |
| "I-WARD": 12, | |
| "O": 13 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 258, | |
| "model_type": "roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "tie_word_embeddings": true, | |
| "tokenizer_class": "PhobertTokenizer", | |
| "transformers_version": "5.9.0", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 64001 | |
| } | |