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fix: force Qwen2TokenizerFast for qwen2 model types #369

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fix: force Qwen2TokenizerFast for qwen2 model types #369

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23 changes: 22 additions & 1 deletion src/heretic/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -73,12 +73,33 @@ def __init__(self, settings: Settings):
print()
print(f"Loading model [bold]{settings.model}[/]...")

self.tokenizer = AutoTokenizer.from_pretrained(
# Load configuration dictionary to verify model type.
# This prevents tokenizers configured with incorrect classes in upstream
# config metadata from generating corrupted/space-stripped tokens.
config_dict, _ = PretrainedConfig.get_config_dict(
settings.model,
trust_remote_code=settings.trust_remote_code,
**self.revision_kwargs,
)

tokenizer_kwargs = {
"trust_remote_code": settings.trust_remote_code,
**self.revision_kwargs,
}

if config_dict.get("model_type") == "qwen2":
from transformers import Qwen2TokenizerFast # ty:ignore[unresolved-import]

self.tokenizer = Qwen2TokenizerFast.from_pretrained(
settings.model,
**tokenizer_kwargs,
Comment on lines +90 to +95

@gemini-code-assist gemini-code-assist Bot Jun 10, 2026

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medium

Checking only for "qwen2" might miss other Qwen2-family model types (such as "qwen2_moe", "qwen2_vl", or "qwen2_audio") which also use the Qwen2 tokenizer and could suffer from similar upstream configuration issues. Checking if the model_type starts with "qwen2" is more robust and future-proof.

Suggested change
if config_dict.get("model_type") == "qwen2":
from transformers import Qwen2TokenizerFast # ty:ignore[unresolved-import]
self.tokenizer = Qwen2TokenizerFast.from_pretrained(
settings.model,
**tokenizer_kwargs,
model_type = config_dict.get("model_type")
if isinstance(model_type, str) and model_type.startswith("qwen2"):
from transformers import Qwen2TokenizerFast
self.tokenizer = Qwen2TokenizerFast.from_pretrained(
settings.model,
**tokenizer_kwargs,
)

)
else:
self.tokenizer = AutoTokenizer.from_pretrained(
settings.model,
**tokenizer_kwargs,
)

# Multimodal models have a processor we'll want to save.
self.processor = None
if get_model_class(settings.model) == AutoModelForImageTextToText:
Expand Down