Instructions to use CS221DoAn/Do_an_group_mBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CS221DoAn/Do_an_group_mBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="CS221DoAn/Do_an_group_mBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("CS221DoAn/Do_an_group_mBERT") model = AutoModelForTokenClassification.from_pretrained("CS221DoAn/Do_an_group_mBERT") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "classifier_dropout": null, | |
| "directionality": "bidi", | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "B-FOOD", | |
| "1": "B-NOTE", | |
| "2": "B-PHONE", | |
| "3": "B-PLACE", | |
| "4": "B-PRICE", | |
| "5": "B-QUANTITY", | |
| "6": "B-TIME", | |
| "7": "I-FOOD", | |
| "8": "I-NOTE", | |
| "9": "I-PHONE", | |
| "10": "I-PLACE", | |
| "11": "I-QUANTITY", | |
| "12": "I-TIME", | |
| "13": "O" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "B-FOOD": 0, | |
| "B-NOTE": 1, | |
| "B-PHONE": 2, | |
| "B-PLACE": 3, | |
| "B-PRICE": 4, | |
| "B-QUANTITY": 5, | |
| "B-TIME": 6, | |
| "I-FOOD": 7, | |
| "I-NOTE": 8, | |
| "I-PHONE": 9, | |
| "I-PLACE": 10, | |
| "I-QUANTITY": 11, | |
| "I-TIME": 12, | |
| "O": 13 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.0.0", | |
| "type_vocab_size": 2, | |
| "use_cache": false, | |
| "vocab_size": 119547 | |
| } | |