Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
Korean
electra
Generated from Trainer
Instructions to use Leo97/KoELECTRA-small-v3-modu-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Leo97/KoELECTRA-small-v3-modu-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Leo97/KoELECTRA-small-v3-modu-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Leo97/KoELECTRA-small-v3-modu-ner") model = AutoModelForTokenClassification.from_pretrained("Leo97/KoELECTRA-small-v3-modu-ner", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download config.json from Leo97/KoELECTRA-small-v3-modu-ner: direct link, hf CLI and curl.
- Browser
- Download file 1.88 kB
-
https://huggingface.co/Leo97/KoELECTRA-small-v3-modu-ner/resolve/main/config.json
- Command line
-
hf download hf://Leo97/KoELECTRA-small-v3-modu-ner/config.json
-
curl -L -o config.json https://huggingface.co/Leo97/KoELECTRA-small-v3-modu-ner/resolve/main/config.json
1.88 kB
| { | |
| "_name_or_path": "monologg/koelectra-small-v3-discriminator", | |
| "architectures": [ | |
| "ElectraForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "embedding_size": 128, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 256, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-PS", | |
| "2": "I-PS", | |
| "3": "B-FD", | |
| "4": "I-FD", | |
| "5": "B-TR", | |
| "6": "I-TR", | |
| "7": "B-AF", | |
| "8": "I-AF", | |
| "9": "B-OG", | |
| "10": "I-OG", | |
| "11": "B-LC", | |
| "12": "I-LC", | |
| "13": "B-CV", | |
| "14": "I-CV", | |
| "15": "B-DT", | |
| "16": "I-DT", | |
| "17": "B-TI", | |
| "18": "I-TI", | |
| "19": "B-QT", | |
| "20": "I-QT", | |
| "21": "B-EV", | |
| "22": "I-EV", | |
| "23": "B-AM", | |
| "24": "I-AM", | |
| "25": "B-PT", | |
| "26": "I-PT", | |
| "27": "B-MT", | |
| "28": "I-MT", | |
| "29": "B-TM", | |
| "30": "I-TM" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1024, | |
| "label2id": { | |
| "O": 0, | |
| "B-PS": 1, | |
| "I-PS": 2, | |
| "B-FD": 3, | |
| "I-FD": 4, | |
| "B-TR": 5, | |
| "I-TR": 6, | |
| "B-AF": 7, | |
| "I-AF": 8, | |
| "B-OG": 9, | |
| "I-OG": 10, | |
| "B-LC": 11, | |
| "I-LC": 12, | |
| "B-CV": 13, | |
| "I-CV": 14, | |
| "B-DT": 15, | |
| "I-DT": 16, | |
| "B-TI": 17, | |
| "I-TI": 18, | |
| "B-QT": 19, | |
| "I-QT": 20, | |
| "B-EV": 21, | |
| "I-EV": 22, | |
| "B-AM": 23, | |
| "I-AM": 24, | |
| "B-PT": 25, | |
| "I-PT": 26, | |
| "B-MT": 27, | |
| "I-MT": 28, | |
| "B-TM": 29, | |
| "I-TM": 30 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "electra", | |
| "num_attention_heads": 4, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "summary_activation": "gelu", | |
| "summary_last_dropout": 0.1, | |
| "summary_type": "first", | |
| "summary_use_proj": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.27.4", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 35000 | |
| } | |