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fix(bridge): remove orphaned convert_weights override from nanogpt adapter #1602

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Merged
jlarson4 merged 1 commit into from
Aug 4, 2026
Merged

fix(bridge): remove orphaned convert_weights override from nanogpt adapter #1602

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15 changes: 0 additions & 15 deletions transformer_lens/model_bridge/supported_architectures/nanogpt.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,5 @@
from typing import Any

import torch

from transformer_lens.conversion_utils.conversion_steps import RearrangeTensorConversion
from transformer_lens.conversion_utils.param_processing_conversion import (
ParamProcessingConversion,
Expand Down Expand Up @@ -88,16 +86,3 @@ def __init__(self, cfg: Any) -> None:
), # Final layer norm
"unembed": UnembeddingBridge(name="lm_head"),
}

def convert_weights(self, remote_module: Any) -> dict[str, torch.Tensor]:
# Nanogpt models saved after torch.compile() have this unwanted prefix
# This is a simple way to remove it
unwanted_prefix = "_orig_mod."
state_dict: dict[str, torch.Tensor] = (
remote_module.state_dict() if hasattr(remote_module, "state_dict") else remote_module
)
for k, v in list(state_dict.items()):
if k.startswith(unwanted_prefix):
state_dict[k[len(unwanted_prefix) :]] = state_dict.pop(k)

return super().convert_weights(remote_module) # type: ignore[misc]
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