sgl-project/sglang · error · ValueError

Failed to load mistral '{config_file_name}' config for model

Error message

Failed to load mistral '{config_file_name}' config for model {model}. Please check if the model is a mistral-format model and if the config file exists.

What it means

After reading params.json for a Mistral-format model, the parsed config came back None/empty, so the model is likely not Mistral-format or the params.json is malformed. Note the code path makes this reachable mainly when the JSON file parses to null.

Source

Thrown at python/sglang/srt/utils/hf_transformers/mistral_utils.py:312

    return config


class MistralConfigParser:
    def get_hf_file_to_dict(
        self, file_name: str, model: str | Path, revision: str | None = "main"
    ):
        file_path = Path(model) / file_name
        if not file_path.is_file():
            raise FileNotFoundError(f"File not found {model}, {file_name}")

        with open(file_path) as file:
            return json.load(file)

    def _download_mistral_config_file(self, model, revision) -> dict:
        config_file_name = "params.json"
        config_dict = self.get_hf_file_to_dict(config_file_name, model, revision)
        if config_dict is None:
            raise ValueError(
                f"Failed to load mistral '{config_file_name}' config for model "
                f"{model}. Please check if the model is a mistral-format model "
                f"and if the config file exists."
            )
        assert isinstance(config_dict, dict)
        return config_dict

    def parse(
        self,
        model: str | Path,
        revision: str | None = None,
        **kwargs,
    ) -> tuple[dict, PretrainedConfig]:
        config_dict = self._download_mistral_config_file(model, revision)
        if config_dict.get("max_position_embeddings") is None:
            logger.warning(
                "The params.json file is missing 'max_position_embeddings'"
                " and could not get a value from the HF config."

View on GitHub (pinned to 0132848349)

Solutions

1. Inspect params.json in the model dir and confirm it is a non-null JSON object
2. Re-download the model snapshot (hf download / huggingface-cli) to repair corrupted files
3. Use the HF-format variant of the model

import json; d = json.load(open(Path(model)/'params.json'))
assert isinstance(d, dict) and d

When it happens

Trigger: A params.json that literally contains 'null' or is emptied out, while --model-config-parser mistral is active.

Common situations: Corrupted or placeholder params.json in a partially downloaded model directory.

Related errors

• Found unknown quantization='{quantization}' in config
• File not found {model}, {file_name}
• This browser cannot encode H.264 MP4
• H.264 encoder did not return MP4 decoder config
• This browser does not support gzip stream decoding

AI-assisted analysis of sgl-project/sglang@0132848349 (2026-08-28). Data as JSON: /api/errors/3be5255608c258d0. Report an issue: GitHub.