huggingface/transformers · error · ValueError

Must have at least `1` token to score after the first min_pr

Error message

Must have at least `1` token to score after the first min_prefix_len={self.processor.context_width} tokens required by the seeding scheme.

What it means

Error "Must have at least `1` token to score after the first min_prefix_len={self.processor.context_width} tokens required by the seeding scheme." thrown in huggingface/transformers.

Source

Thrown at src/transformers/generation/watermarking.py:218

                    The watermark generated text. It is advised to remove the prompt, which can affect the detection.
                z_threshold (`Dict`, *optional*, defaults to `3.0`):
                    Changing this threshold will change the sensitivity of the detector. Higher z threshold gives less
                    sensitivity and vice versa for lower z threshold.
                return_dict (`bool`,  *optional*, defaults to `False`):
                    Whether to return `~generation.WatermarkDetectorOutput` or not. If not it will return boolean predictions,
        ma
                Return:
                    [`~generation.WatermarkDetectorOutput`] or `np.ndarray`: A [`~generation.WatermarkDetectorOutput`]
                    if `return_dict=True` otherwise a `np.ndarray`.

        """

        # Let's assume that if one batch start with `bos`, all batched also do
        if input_ids[0, 0] == self.bos_token_id:
            input_ids = input_ids[:, 1:]

        if input_ids.shape[-1] - self.processor.context_width < 1:
            raise ValueError(
                f"Must have at least `1` token to score after the first "
                f"min_prefix_len={self.processor.context_width} tokens required by the seeding scheme."
            )

        num_tokens_scored, green_token_count = self._score_ngrams_in_passage(input_ids)
        z_score = self._compute_z_score(green_token_count, num_tokens_scored)
        prediction = z_score > z_threshold

        if return_dict:
            p_value = self._compute_pval(z_score)
            confidence = 1 - p_value

            return WatermarkDetectorOutput(
                num_tokens_scored=num_tokens_scored,
                num_green_tokens=green_token_count,
                green_fraction=green_token_count / num_tokens_scored,
                z_score=z_score,
                p_value=p_value,

View on GitHub (pinned to a597f97485)

Solutions

1. Generate at least one token beyond the processor's `context_width` (min_prefix_len).
2. Lower `context_width` or increase `min_new_tokens` so scoring has tokens to work on.

When it happens

Trigger: Raised in watermarking score computation when fewer than one token remains after the seeding scheme's required min_prefix_len context.

Common situations: Watermark detection on very short texts shorter than the processor's context_width requirement.

AI-assisted analysis of huggingface/transformers@a597f97485 (2026-08-14). Data as JSON: /api/errors/178ea27d19ad666b. Report an issue: GitHub.