Token Classification
Transformers
Safetensors
PyTorch
bert
ner
turkish
tr
dbmdz
bert-base-cased
bert-base-turkish-cased
Instructions to use nextgeo/address-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nextgeo/address-extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nextgeo/address-extraction")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nextgeo/address-extraction") model = AutoModelForTokenClassification.from_pretrained("nextgeo/address-extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from nextgeo/address-extraction: direct link, hf CLI and curl.
- Browser
- Download file 2.04 kB
-
https://huggingface.co/nextgeo/address-extraction/resolve/06410f5ed0cd054dc2169bc982c6f074a7067733/config.json
- Command line
-
hf download hf://nextgeo/address-extraction@06410f5ed0cd054dc2169bc982c6f074a7067733/config.json
-
curl -L -o config.json https://huggingface.co/nextgeo/address-extraction/resolve/06410f5ed0cd054dc2169bc982c6f074a7067733/config.json
2.04 kB
| { | |
| "_name_or_path": "dbmdz/bert-base-turkish-cased", | |
| "architectures": [ | |
| "BertForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1", | |
| "2": "LABEL_2", | |
| "3": "LABEL_3", | |
| "4": "LABEL_4", | |
| "5": "LABEL_5", | |
| "6": "LABEL_6", | |
| "7": "LABEL_7", | |
| "8": "LABEL_8", | |
| "9": "LABEL_9", | |
| "10": "LABEL_10", | |
| "11": "LABEL_11", | |
| "12": "LABEL_12", | |
| "13": "LABEL_13", | |
| "14": "LABEL_14", | |
| "15": "LABEL_15", | |
| "16": "LABEL_16", | |
| "17": "LABEL_17", | |
| "18": "LABEL_18", | |
| "19": "LABEL_19", | |
| "20": "LABEL_20", | |
| "21": "LABEL_21", | |
| "22": "LABEL_22", | |
| "23": "LABEL_23", | |
| "24": "LABEL_24", | |
| "25": "LABEL_25", | |
| "26": "LABEL_26", | |
| "27": "LABEL_27", | |
| "28": "LABEL_28", | |
| "29": "LABEL_29", | |
| "30": "LABEL_30", | |
| "31": "LABEL_31", | |
| "32": "LABEL_32" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1, | |
| "LABEL_10": 10, | |
| "LABEL_11": 11, | |
| "LABEL_12": 12, | |
| "LABEL_13": 13, | |
| "LABEL_14": 14, | |
| "LABEL_15": 15, | |
| "LABEL_16": 16, | |
| "LABEL_17": 17, | |
| "LABEL_18": 18, | |
| "LABEL_19": 19, | |
| "LABEL_2": 2, | |
| "LABEL_20": 20, | |
| "LABEL_21": 21, | |
| "LABEL_22": 22, | |
| "LABEL_23": 23, | |
| "LABEL_24": 24, | |
| "LABEL_25": 25, | |
| "LABEL_26": 26, | |
| "LABEL_27": 27, | |
| "LABEL_28": 28, | |
| "LABEL_29": 29, | |
| "LABEL_3": 3, | |
| "LABEL_30": 30, | |
| "LABEL_31": 31, | |
| "LABEL_32": 32, | |
| "LABEL_4": 4, | |
| "LABEL_5": 5, | |
| "LABEL_6": 6, | |
| "LABEL_7": 7, | |
| "LABEL_8": 8, | |
| "LABEL_9": 9 | |
| }, | |
| "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": "4.37.0", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |