huggingface input_error ai_generated true

Token indices sequence length is longer than the specified maximum sequence length for this model (2048 > 512). Running this sequence through the model will result in indexing errors

ID: huggingface/tokenizer-max-length-exceeded

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90%Fix Rate
90%Confidence
3Evidence
2023-01-01First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
any active — — —

Root Cause

Input text tokenizes to more tokens than the model's maximum sequence length. Causes indexing errors or silent truncation.

generic

Workarounds

  1. 95% success Enable truncation in the tokenizer call 
    tokens = tokenizer(text, truncation=True, max_length=512, return_tensors='pt')

    Sources: https://huggingface.co/docs/transformers/

  2. 88% success Split long texts into overlapping chunks and process separately 
    Use a sliding window: chunk text with stride < max_length, process each chunk, aggregate results
  3. 82% success Use a model variant with longer context support 
    E.g., use 'model-name-16k' or 'model-name-32k' variants, or models with ALiBi/RoPE for longer contexts

Dead Ends

Common approaches that don't work:

  1. Increase model_max_length on the tokenizer object 88% fail

    The model's positional embeddings are fixed at training time. Increasing tokenizer max length does not change what the model can process.

  2. Ignore the warning assuming the model handles it internally 82% fail

    The model will produce indexing errors or garbage outputs for tokens beyond its position embedding range.