Text Classification
Transformers
PyTorch
Chinese
bert
Argument_Type_Bert
zh-tw
Generated from Trainer
text-embeddings-inference
Instructions to use theta/Argument_Type_Bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theta/Argument_Type_Bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="theta/Argument_Type_Bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("theta/Argument_Type_Bert") model = AutoModelForSequenceClassification.from_pretrained("theta/Argument_Type_Bert") - Notebooks
- Google Colab
- Kaggle
End of training
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{"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "bert-base-chinese", "tokenizer_class": "BertTokenizer"}
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