Text Classification
Transformers
Safetensors
English
bert
fill-mask
question-answering
evaluation
text
Instructions to use zli12321/answer_equivalence_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zli12321/answer_equivalence_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zli12321/answer_equivalence_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("zli12321/answer_equivalence_bert") model = AutoModelForMaskedLM.from_pretrained("zli12321/answer_equivalence_bert") - Notebooks
- Google Colab
- Kaggle
Zongxia Li commited on
Delete special_tokens_map.json
Browse files- special_tokens_map.json +0 -7
special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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