vocab/llama/README.md

tokenizer.json 和 tokenizer.model 是 都需要吗？

完整性

以下 256个字符保证了词典的完整性

    "vocab": {
      "<0x00>": 3,
      "<0x01>": 4,
      ...
      "<0xFE>": 257,
      "<0xFF>": 258,

  "normalizer": {
    "type": "Sequence",
    "normalizers": [
      {
        "type": "Prepend",
        "prepend": "▁"
      },
      {
        "type": "Replace",
        "pattern": {
          "String": " "
        },
        "content": "▁"
      }
    ]
  },

  "post_processor": {
    "type": "TemplateProcessing",
    "single": [
      {
        "SpecialToken": {
          "id": "<s>",
          "type_id": 0
        }
      },
      {
        "Sequence": {
          "id": "A",
          "type_id": 0
        }
      }
    ],
    "pair": [
      {
        "SpecialToken": {
          "id": "<s>",
          "type_id": 0
        }
      },
      {
        "Sequence": {
          "id": "A",
          "type_id": 0
        }
      },
      {
        "Sequence": {
          "id": "B",
          "type_id": 0
        }
      }
    ],
    "special_tokens": {
      "<s>": {
        "id": "<s>",
        "ids": [
          1
        ],
        "tokens": [
          "<s>"
        ]
      }
    }
  },
  "decoder": {
    "type": "Sequence",
    "decoders": [
      {
        "type": "Replace",
        "pattern": {
          "String": "▁"
        },
        "content": " "
      },
      {
        "type": "ByteFallback"
      },
      {
        "type": "Fuse"
      },
      {
        "type": "Strip",
        "content": " ",
        "start": 1,
        "stop": 0
      }
    ]
  },

issues

1. https://github.com/LianjiaTech/BELLE/issues/45 llama 700个中文只是显式支持的数量，隐含支持的unicode中文字远超700， 你可以随便用一个bert的词表做实验。不过恶心的是这样一个中文字就会encode成4,5个unicode toekn，长度一下就上去了，所以还是哈工大做中文词表增强的靠谱。

2. https://github.com/LianjiaTech/BELLE/issues/43 请问各位llama在中文上使用需要对词表做额外操作吗？ 应该是要的，我测了一下llama词表和常用汉字3500个的交集，只有600多个。增加词表可参考https://github.com/ymcui/Chinese-LLaMA-Alpaca