huggingface config_error ai_generated true

ValueError: Adding special tokens to a tokenizer that already has them; use `add_special_tokens=True` only if you intend to add new tokens. Got extra_ids=0 but tokenizer already has 2 special tokens.

ID: huggingface/tokenizer-extra-special-tokens-invalid

Also available as: JSON · Markdown · 中文
90%Fix Rate
84%Confidence
1Evidence
2024-05-12First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
tokenizers 0.19.1 active — — —
transformers 4.44.0 active — — —

Root Cause

User called `tokenizer.add_special_tokens()` with an empty or redundant special tokens dictionary, but the tokenizer already has those tokens defined, causing a validation error.

generic

中文

用户使用空的或冗余的特殊标记字典调用了 `tokenizer.add_special_tokens()`，但分词器已定义这些标记，导致验证错误。

Official Documentation

https://huggingface.co/docs/tokenizers/en/api/special-tokens

Workarounds

  1. 90% success Check existing special tokens before adding: if `tokenizer.special_tokens_map` already contains the tokens, skip the `add_special_tokens` call entirely. 
    Check existing special tokens before adding: if `tokenizer.special_tokens_map` already contains the tokens, skip the `add_special_tokens` call entirely.
  2. 85% success Use `tokenizer.add_special_tokens({'additional_special_tokens': ['<new_token>']})` only for truly new tokens, not duplicates. 
    Use `tokenizer.add_special_tokens({'additional_special_tokens': ['<new_token>']})` only for truly new tokens, not duplicates.

中文步骤

  1. Check existing special tokens before adding: if `tokenizer.special_tokens_map` already contains the tokens, skip the `add_special_tokens` call entirely.
  2. Use `tokenizer.add_special_tokens({'additional_special_tokens': ['<new_token>']})` only for truly new tokens, not duplicates.

Dead Ends

Common approaches that don't work:

  1. 100% fail

    The parameter `add_special_tokens` controls whether to add tokens to the vocabulary, not whether to check for duplicates; the error persists.

  2. 40% fail

    Deleting built-in special tokens (like [CLS], [SEP]) can break tokenizer functionality; re-adding may still fail if they are already present in the base tokenizer.