Instructions to use sofom/bert-base-uncased-turingbench-aa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sofom/bert-base-uncased-turingbench-aa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sofom/bert-base-uncased-turingbench-aa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sofom/bert-base-uncased-turingbench-aa") model = AutoModelForSequenceClassification.from_pretrained("sofom/bert-base-uncased-turingbench-aa") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
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"special": true
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}
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},
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"clean_up_tokenization_spaces":
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"special": true
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}
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},
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"clean_up_tokenization_spaces": false,
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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