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[Regression] Qwen3.5 saved checkpoint is not correct with save_pretrained API since version 5.4.0 #45216
transformers == 5.3.0 works well
transformers ==5.4.0 returns Unexpected model.language_model.language_model.language_model.layers.7.self_attn.v_proj.weight in loaded safetensors file
An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
My own task or dataset (give details below)
Reproduction
import transformers
name = "Qwen/Qwen3.5-0.8B"
model = transformers.Qwen3_5ForConditionalGeneration.from_pretrained(name, trust_remote_code=True)
model.save_pretrained("./qwen-35")
from safetensors.torch import save_file, load_file
loaded = load_file("./qwen-35/model.safetensors")
assert not 'model.language_model.language_model.language_model.layers.7.self_attn.v_proj.weight' in loaded, "Unexpected model.language_model.language_model.language_model.layers.7.self_attn.v_proj.weight in loaded safetensors file"
Oh no, some conversions are meant to be applied only for certain classes. A quick workaround could be to bring back the cls attribute for conversion_mapping though as I mentioned earlier to @Cyrilvallez imo we need a better way to store conversions. We have several regex patterns that are model-class specific, for ex applied only when a prediction is present
Ig in long term we have to adjust conversion dict's layout slightly
Activity
fix: skip qwen3_5_text checkpoint remap for nested VL language_model …
zucchini-nlp commentedon Apr 7, 2026
Oh no, some conversions are meant to be applied only for certain classes. A quick workaround could be to bring back the cls attribute for
conversion_mappingthough as I mentioned earlier to @Cyrilvallez imo we need a better way to store conversions. We have several regex patterns that are model-class specific, for ex applied only when a prediction is presentIg in long term we have to adjust conversion dict's layout slightly