Token Classification
Transformers
Safetensors
PyTorch
Thai
camembert
ner
thai
phayathaibert
phayathaibert-thainer
Eval Results (legacy)
Instructions to use JonusNattapong/OpenThai-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JonusNattapong/OpenThai-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="JonusNattapong/OpenThai-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("JonusNattapong/OpenThai-NER") model = AutoModelForTokenClassification.from_pretrained("JonusNattapong/OpenThai-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 632fec6b75abba129c09ade718792b9dc914650f0f2842a0ad888ba049f30ea2
- Size of remote file:
- 17.3 MB
- SHA256:
- 616a8b047d1587dc2608c12e495431986cdb509c7db87e343d99a41e60d5e14a
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