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 tokenizer_config.json from Leo97/KoELECTRA-small-v3-modu-ner: direct link, hf CLI and curl.
- Browser
- Download file 365 Bytes
-
https://huggingface.co/Leo97/KoELECTRA-small-v3-modu-ner/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Leo97/KoELECTRA-small-v3-modu-ner/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Leo97/KoELECTRA-small-v3-modu-ner/resolve/main/tokenizer_config.json
365 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": false, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 512, | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "special_tokens_map_file": null, | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "ElectraTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |