# Token indices sequence length is longer than the specified maximum sequence length for this model (2048 > 1024). Running out-of-order

- **ID:** `huggingface/tokenizer-decoder-max-length-overflow`
- **Domain:** huggingface
- **Category:** runtime_error
- **Verification:** ai_generated
- **Fix Rate:** 85%

## Root Cause

Input text is too long for the model's max_position_embeddings, causing tokenizer to truncate incorrectly or overflow without proper truncation settings.

## Version Compatibility

| Version | Status | Introduced | Deprecated |
|---------|--------|------------|------------|
| transformers>=4.30.0 | active | — | — |
| tokenizers>=0.13.0 | active | — | — |
| python>=3.8 | active | — | — |

## Workarounds

1. **Set truncation=True and max_length=512 when encoding inputs. Example: tokenizer(text, truncation=True, max_length=512, return_tensors='pt')** (90% success)
   ```
   Set truncation=True and max_length=512 when encoding inputs. Example: tokenizer(text, truncation=True, max_length=512, return_tensors='pt')
   ```
2. **Use a model with larger max_position_embeddings (e.g., 4096) or switch to a long-context model like Longformer.** (80% success)
   ```
   Use a model with larger max_position_embeddings (e.g., 4096) or switch to a long-context model like Longformer.
   ```

## Dead Ends

- **** — truncation=False disables truncation entirely, leading to a hard crash rather than graceful handling. (60% fail)
- **** — Model's learned positional embeddings only support up to max_position_embeddings; exceeding it leads to out-of-range errors. (80% fail)