tensorflow/models · error · ValueError
Must set vocab_file or sp_model_file.
Error message
Must set vocab_file or sp_model_file.
What it means
Error "Must set vocab_file or sp_model_file." thrown in tensorflow/models.
Source
Thrown at official/nlp/tools/export_tfhub_lib.py:74
return bert_encoder
def get_do_lower_case(do_lower_case, vocab_file=None, sp_model_file=None):
"""Returns do_lower_case, replacing None by a guess from vocab file name."""
if do_lower_case is not None:
return do_lower_case
elif vocab_file:
do_lower_case = "uncased" in vocab_file
logging.info("Using do_lower_case=%s based on name of vocab_file=%s",
do_lower_case, vocab_file)
return do_lower_case
elif sp_model_file:
do_lower_case = True # All public ALBERTs (as of Oct 2020) do it.
logging.info("Defaulting to do_lower_case=%s for Sentencepiece tokenizer",
do_lower_case)
return do_lower_case
else:
raise ValueError("Must set vocab_file or sp_model_file.")
def _create_model(
*,
bert_config: Optional[configs.BertConfig] = None,
encoder_config: Optional[encoders.EncoderConfig] = None,
with_mlm: bool,
) -> Tuple[tf_keras.Model, tf_keras.Model]:
"""Creates the model to export and the model to restore the checkpoint.
Args:
bert_config: A legacy `BertConfig` to create a `BertEncoder` object. Exactly
one of encoder_config and bert_config must be set.
encoder_config: An `EncoderConfig` to create an encoder of the configured
type (`BertEncoder` or other).
with_mlm: A bool to control the second component of the result. If True,
will create a `BertPretrainerV2` object; otherwise, will create a
`BertEncoder` object.View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/nlp/tools/export_tfhub_lib.py:74 when the library encounters an invalid state.
Common situations: See trigger scenarios.
AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24).
Data as JSON: /api/errors/3bb8bb6d5c09905e.
Report an issue: GitHub.