Token Classification
Transformers
Safetensors
Turkish
bert
ner
turkish
academic
anonymization
kvkk
berturk
tr-academic-nlp
Instructions to use hakansabunis/trakad-ner-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hakansabunis/trakad-ner-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hakansabunis/trakad-ner-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hakansabunis/trakad-ner-v1") model = AutoModelForTokenClassification.from_pretrained("hakansabunis/trakad-ner-v1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-YAZAR", | |
| "2": "I-YAZAR", | |
| "3": "B-KURUM", | |
| "4": "I-KURUM", | |
| "5": "B-YIL", | |
| "6": "I-YIL", | |
| "7": "B-METODOLOJI", | |
| "8": "I-METODOLOJI", | |
| "9": "B-DATASET", | |
| "10": "I-DATASET", | |
| "11": "B-METR\u0130K", | |
| "12": "I-METR\u0130K", | |
| "13": "B-DERG\u0130", | |
| "14": "I-DERG\u0130" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "B-DATASET": 9, | |
| "B-DERG\u0130": 13, | |
| "B-KURUM": 3, | |
| "B-METODOLOJI": 7, | |
| "B-METR\u0130K": 11, | |
| "B-YAZAR": 1, | |
| "B-YIL": 5, | |
| "I-DATASET": 10, | |
| "I-DERG\u0130": 14, | |
| "I-KURUM": 4, | |
| "I-METODOLOJI": 8, | |
| "I-METR\u0130K": 12, | |
| "I-YAZAR": 2, | |
| "I-YIL": 6, | |
| "O": 0 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.5.0", | |
| "type_vocab_size": 2, | |
| "use_cache": false, | |
| "vocab_size": 32000 | |
| } | |