Instructions to use yongsun-yoon/mdeberta-v3-base-open-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yongsun-yoon/mdeberta-v3-base-open-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="yongsun-yoon/mdeberta-v3-base-open-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("yongsun-yoon/mdeberta-v3-base-open-ner") model = AutoModelForTokenClassification.from_pretrained("yongsun-yoon/mdeberta-v3-base-open-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Open Named Entity Recognition (Multilingual)
You can read the details in this post.
from transformers import pipeline
nlp = pipeline('token-classification', 'yongsun-yoon/deberta-v3-base-open-ner', aggregation_strategy='simple')
text = '30์ผ ์ ์ฃผ์ง๋ฒ ๊ตฐ์ฐ์ง์ ์ 1ํ์ฌ๋ถ๋ ๋ฐ ์์ฅ์ ๋ํ ์ ๊ณ ๊ณตํ์์ ๋ฒ๊ธ 500๋ง์์ ์ ๊ณ ํ๋ค.'
entity_type = 'event'
input_text = f'{text}{nlp.tokenizer.sep_token}{entity_type}' # [SEP]
nlp(input_text) # ์ ๊ณ ๊ณตํ
- Downloads last month
- 3