Instructions to use MikeGreen2710/model_1_address with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MikeGreen2710/model_1_address with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MikeGreen2710/model_1_address")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MikeGreen2710/model_1_address") model = AutoModelForTokenClassification.from_pretrained("MikeGreen2710/model_1_address", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "MikeGreen2710/model_1_address", | |
| "architectures": [ | |
| "RobertaForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "eos_token_id": 2, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "OTHER", | |
| "1": "B_STR", | |
| "2": "I_STR", | |
| "3": "B_LEG", | |
| "4": "B_DIS", | |
| "5": "I_DIS", | |
| "6": "B_CIT", | |
| "7": "I_CIT", | |
| "8": "I_LEG", | |
| "9": "B_WAR", | |
| "10": "I_WAR", | |
| "11": "B_LOC", | |
| "12": "I_LOC", | |
| "13": "B_LAN", | |
| "14": "I_LAN", | |
| "15": "B_NUM", | |
| "16": "I_NUM", | |
| "17": "O" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "B_CIT": 6, | |
| "B_DIS": 4, | |
| "B_LAN": 13, | |
| "B_LEG": 3, | |
| "B_LOC": 11, | |
| "B_NUM": 15, | |
| "B_STR": 1, | |
| "B_WAR": 9, | |
| "I_CIT": 7, | |
| "I_DIS": 5, | |
| "I_LAN": 14, | |
| "I_LEG": 8, | |
| "I_LOC": 12, | |
| "I_NUM": 16, | |
| "I_STR": 2, | |
| "I_WAR": 10, | |
| "O": 17, | |
| "OTHER": 0 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 258, | |
| "model_type": "roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "tokenizer_class": "PhobertTokenizer", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.39.3", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 64001 | |
| } | |