Hello,

I finetuned Gemma 2B with Unsloth. It uses LoRA and merges the weights back into the base model.

When I try to load this model, it gives me the following error:

...
File "/home/ubuntu/projects/cql-ml/.venv/lib/python3.10/site-packages/vlm/model_executor/model_loader.py", line 86, in get _model model. load weights(model_config.model, model_config.download_
config. model, model_ config. download dir,
File "/home/ubuntu/projects/cql-ml/.venv/lib/python3.10/site-packages/vlm/model_executor/models/gemma.py", line 339, in load weights
param = params_dict [name]
KeyError: 'lm_head.weight'

My pytorch_model.bin.index.json looks like this:

{
  "metadata": {
    "total_size": 6060920832
  },
  "weight_map": {
    "lm_head.weight": "pytorch_model-00002-of-00002.bin",
    "model.embed_tokens.weight": "pytorch_model-00001-of-00002.bin",
    "model.layers.0.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
    "model.layers.0.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
    "model.layers.0.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
...

I saw in a few of the other classes a similar check for lm_head.weight so I replicated it in load_weights and the model loads correctly and works as intended. 1 2 3

The modified load_weights function:

1333322

I'm not sure if this is an issue with vllm, or an issue with the output of Unsloth. The model works correctly when load_weights is modified. I don't know what the internals of the model should look like. Any help would be appreciated!

I'm unsure if this is related to #2816

My model is Private, so unfortunately I can't share it. However I found this other model on huggingface that's trained with the same tool with the lm_head.weight in the index.

If the modified load_weights function is the desired fix, I can submit a PR if that will help.

Thank you for the help!