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asude55
/
duyguanalizison25

Text Classification
Transformers
PyTorch
bert
Inference Endpoints
Model card Files Community
1
duyguanalizison25
File size: 2,072 Bytes 
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{
  "version": "0.1",
  "truncation": {
    "max_length": 512,
    "stride": 0,
    "strategy": "longest_first"
  },
  "padding": {
    "strategy": "longest",
    "max_length": 512,
    "pad_to_multiple_of": null
  },
  "added_tokens": [
    {
      "id": 0,
      "content": "[PAD]",
      "single_word": false,
      "lstrip": false,
      "rstrip": false,
      "normalized": false,
      "special": true
    },
    {
      "id": 1,
      "content": "[UNK]",
      "single_word": false,
      "lstrip": false,
      "rstrip": false,
      "normalized": false,
      "special": true
    },
    {
      "id": 2,
      "content": "[CLS]",
      "single_word": false,
      "lstrip": false,
      "rstrip": false,
      "normalized": false,
      "special": true
    },
    {
      "id": 3,
      "content": "[SEP]",
      "single_word": false,
      "lstrip": false,
      "rstrip": false,
      "normalized": false,
      "special": true
    },
    {
      "id": 4,
      "content": "[MASK]",
      "single_word": false,
      "lstrip": false,
      "rstrip": false,
      "normalized": false,
      "special": true
    }
  ],
  "normalizer": {
    "type": "BertNormalizer",
    "clean_text": true,
    "handle_chinese_chars": true,
    "strip_accents": null,
    "lowercase": false
  },
  "pre_tokenizer": {
    "type": "BertPreTokenizer"
  },
  "post_processor": {
    "type": "BertPostProcessor",
    "sep": {
      "type": "AddedToken",
      "content": "[SEP]",
      "single_word": false,
      "lstrip": false,
      "rstrip": false,
      "normalized": false
    },
    "cls": {
      "type": "AddedToken",
      "content": "[CLS]",
      "single_word": false,
      "lstrip": false,
      "rstrip": false,
      "normalized": false
    }
  },
  "decoder": {
    "type": "WordPiece",
    "cleanup": true
  },
  "model": {
    "type": "WordPiece",
    "unk_token": "[UNK]",
    "vocab": {
      "[PAD]": 0,
      "[UNK]": 1,
      "[CLS]": 2,
      "[SEP]": 3,
      "[MASK]": 4,
      "hello": 5,
      "world": 6
    },
    "max_input_chars_per_word": 100
  }
}