invoke-ai/InvokeAI · error · ValueError

Unrecognized SDXL LoRA key prefix: '{full_key}'.

Error message

Unrecognized SDXL LoRA key prefix: '{full_key}'.

What it means

convert_sdxl_keys_to_diffusers_format recognizes SDXL LoRA keys only with known prefixes (lora_, lora_te1_, lora_te2_, etc.). Any key with an unrecognized prefix causes this ValueError, because the converter cannot know which model component the tensor targets.

Source

Thrown at invokeai/backend/patches/lora_conversions/sdxl_lora_conversion_utils.py:54

        if full_key.startswith("lora_unet_"):
            search_key = full_key.replace("lora_unet_", "")
            # Use bisect to find the key in stability_unet_keys that *may* match the search_key's prefix.
            position = bisect.bisect_right(stability_unet_keys, search_key)
            map_key = stability_unet_keys[position - 1]
            # Now, check if the map_key *actually* matches the search_key.
            if search_key.startswith(map_key):
                new_key = full_key.replace(map_key, SDXL_UNET_STABILITY_TO_DIFFUSERS_MAP[map_key])
                new_state_dict[new_key] = value
                converted_count += 1
            else:
                new_state_dict[full_key] = value
                not_converted_count += 1
        elif full_key.startswith("lora_te1_") or full_key.startswith("lora_te2_"):
            # The CLIP text encoders have the same keys in both Stability AI and diffusers formats.
            new_state_dict[full_key] = value
            continue
        else:
            raise ValueError(f"Unrecognized SDXL LoRA key prefix: '{full_key}'.")

    if converted_count > 0 and not_converted_count > 0:
        raise ValueError(
            f"The SDXL LoRA could only be partially converted to diffusers format. converted={converted_count},"
            f" not_converted={not_converted_count}"
        )

    return new_state_dict


# code from
# https://github.com/bmaltais/kohya_ss/blob/2accb1305979ba62f5077a23aabac23b4c37e935/networks/lora_diffusers.py#L15C1-L97C32
def _make_sdxl_unet_conversion_map() -> List[Tuple[str, str]]:
    """Create a dict mapping state_dict keys from Stability AI SDXL format to diffusers SDXL format."""
    unet_conversion_map_layer: list[tuple[str, str]] = []

    for i in range(3):  # num_blocks is 3 in sdxl
        # loop over downblocks/upblocks

View on GitHub (pinned to 0b6a024f2f)

Solutions

1. Print the offending key and confirm the file is actually an SDXL LoRA; if not, load it with the converter for its real base model.
2. Rename the key to a supported prefix (e.g. 'lora_unet_...' or 'lora_te_...') matching the SDXL convention.
3. Update/patch the conversion utility to handle the new prefix if the trainer's format is legitimately new.

Example fix

// before
'my_custom_model.blocks.0.lora_down.weight': t
// after (SDXL convention)
'lora_unet_blocks_0_lora_down.weight': t

SUPPORTED = ('lora_', 'lora_te1_', 'lora_te2_')
bad = [k for k in state_dict if not any(k.startswith(p) for p in SUPPORTED)]
if bad:
    raise ValueError(f'keys with unsupported prefixes: {bad[:5]}')

def is_sdxl_lora_state_dict(state_dict: dict[str, object]) -> bool:
    return all(isinstance(k, str) and k.startswith(('lora_', 'lora_te1_', 'lora_te2_')) for k in state_dict)

try:
    sd = convert_sdxl_keys_to_diffusers_format(state_dict)
except ValueError as e:
    if str(e).startswith('Unrecognized SDXL LoRA key prefix'):
        logger.error('Wrong model family or mangled key: %s', e)
        # route to the correct converter for the file's base model
    else:
        raise

When it happens

Trigger: Calling convert_sdxl_keys_to_diffusers_format (via the SDXL LoRA _load_model path) with a state dict containing a key that starts with none of the supported prefixes, e.g. an unrelated model's key or a novel trainer's naming scheme.

Common situations: Loading an SD1/SD3/Flux LoRA with the SDXL converter; files with custom or vendor-specific prefixes; renamed/mangled keys from a state-dict preprocessing step; LyCORIS keys with unusual module names.

Related errors

• Unsupported lora format: {state_dict.keys()}
• Key '{k}' does not match the expected pattern for FLUX LoRA
• Key '{key}' does not match the expected pattern for xlabs FL
• Key {key} does not match parsing tree {parsing_tree}.
• The SDXL LoRA could only be partially converted to diffusers

AI-assisted analysis of invoke-ai/InvokeAI@0b6a024f2f (2026-08-29). Data as JSON: /api/errors/98573095593408a6. Report an issue: GitHub.