Merging fails with RuntimeError: weight required but not present in model

[w601sxs]

I'm trying to merge some embedding models with this config file. the architectures are similar but I think it is erroring out on some names of layers? Would love some suggestions on how to change the yaml to make it work.

YAML config:

models:
  - model: mixedbread-ai/mxbai-embed-large-v1
  - model: BAAI/bge-large-en-v1.5
    parameters:
      density: [0, 0.25, 0.5, 0.75, 1]
      weight: [0, 0.25, 0.5, 0.75, 1]
  - model: avsolatorio/GIST-large-Embedding-v0
    parameters:
      density: [0, 0.25, 0.5, 0.75, 1]
      weight: [0, 0.25, 0.5, 0.75, 1]
  - model: WhereIsAI/UAE-Large-V1
    parameters:
      density: [0, 0.25, 0.5, 0.75, 1]
      weight: [0, 0.25, 0.5, 0.75, 1]
merge_method: dare_ties
base_model: mixedbread-ai/mxbai-embed-large-v1
parameters:
  int8_mask: true
dtype: bfloat16

Error

RuntimeError: Tensor bert.encoder.layer.23.output.LayerNorm.weight required but not present in model WhereIsAI/UAE-Large-V1

CLI used

!mergekit-yaml merge.yaml ./output --cuda