Instructions to use Hyoungjun-yk/legal-instrument-doro-ner-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hyoungjun-yk/legal-instrument-doro-ner-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Hyoungjun-yk/legal-instrument-doro-ner-finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Hyoungjun-yk/legal-instrument-doro-ner-finetuned") model = AutoModelForTokenClassification.from_pretrained("Hyoungjun-yk/legal-instrument-doro-ner-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "BertForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "B-BLD_NAME", | |
| "1": "B-BLD_NAME_DONG", | |
| "2": "B-BLD_NAME_HO", | |
| "3": "B-LOC_DO", | |
| "4": "B-LOC_DONG", | |
| "5": "B-LOC_GU", | |
| "6": "B-LOC_SI", | |
| "7": "B-ROAD", | |
| "8": "B-ROAD_NO", | |
| "9": "I-BLD_NAME", | |
| "10": "I-BLD_NAME_DONG", | |
| "11": "I-BLD_NAME_HO", | |
| "12": "I-LOC_DO", | |
| "13": "I-LOC_DONG", | |
| "14": "I-LOC_GU", | |
| "15": "I-LOC_SI", | |
| "16": "I-ROAD", | |
| "17": "I-ROAD_NO", | |
| "18": "NAME", | |
| "19": "O" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "B-BLD_NAME": 0, | |
| "B-BLD_NAME_DONG": 1, | |
| "B-BLD_NAME_HO": 2, | |
| "B-LOC_DO": 3, | |
| "B-LOC_DONG": 4, | |
| "B-LOC_GU": 5, | |
| "B-LOC_SI": 6, | |
| "B-ROAD": 7, | |
| "B-ROAD_NO": 8, | |
| "I-BLD_NAME": 9, | |
| "I-BLD_NAME_DONG": 10, | |
| "I-BLD_NAME_HO": 11, | |
| "I-LOC_DO": 12, | |
| "I-LOC_DONG": 13, | |
| "I-LOC_GU": 14, | |
| "I-LOC_SI": 15, | |
| "I-ROAD": 16, | |
| "I-ROAD_NO": 17, | |
| "NAME": 18, | |
| "O": 19 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.52.4", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |