Text Classification
Transformers
PyTorch
English
Chinese
bert
fill-mask
chinese
traditional-chinese
Eval Results (legacy)
text-embeddings-inference
Instructions to use renhehuang/bert-traditional-chinese-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use renhehuang/bert-traditional-chinese-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="renhehuang/bert-traditional-chinese-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("renhehuang/bert-traditional-chinese-classifier") model = AutoModelForMaskedLM.from_pretrained("renhehuang/bert-traditional-chinese-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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