Instructions to use Bharat2004/factchecker-deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bharat2004/factchecker-deberta with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Bharat2004/factchecker-deberta", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer.json +0 -0
- tokenizer_config.json +6 -15
tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": true,
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"backend": "tokenizers",
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"bos_token": "[CLS]",
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"cls_token": "[CLS]",
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"do_lower_case":
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"eos_token": "[SEP]",
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"extra_special_tokens": [
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"[PAD]",
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"[CLS]",
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"[SEP]"
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],
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"is_local": false,
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"mask_token": "[MASK]",
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"model_max_length":
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"
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"
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"
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"unk_token": "[UNK]"
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"vocab_type": "spm"
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}
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{
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"backend": "tokenizers",
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"is_local": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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