Instructions to use kobkrit/wangchanberta-ner-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kobkrit/wangchanberta-ner-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kobkrit/wangchanberta-ner-2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kobkrit/wangchanberta-ner-2") model = AutoModelForTokenClassification.from_pretrained("kobkrit/wangchanberta-ner-2") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("kobkrit/wangchanberta-ner-2")
model = AutoModelForTokenClassification.from_pretrained("kobkrit/wangchanberta-ner-2")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kobkrit/wangchanberta-ner-2")