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Training LLMs with QLoRA + FSDP
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`Converting the State Dict.ipynb` - Runtine error because Unexpected keys #70

Closed chwenjun225 closed 2 months ago

chwenjun225 commented 2 months ago

I was successfully finetune my data with llama2-7b-hf, then save model trained as model_state_dict.safetensors, and then I use Converting the State Dict.ipynb. It get Runtime Error when I run peft_model.load_state_dict(new_sd)

{ "name": "RuntimeError", "message": "Error(s) in loading state_dict for PeftModelForCausalLM: \tUnexpected key(s) in state_dict: \"base_model.model.model.layers.0.self_attn.q_proj.base_layer.weight.absmax\", \"base_model.model.model.layers.0.self_attn.q_proj.base_layer.weight.quant_map\", \"base_model.model.model.layers.0.self_attn.q_proj.base_layer.weight.quant_state.bitsandbytesnf4\", \"base_model.model.model.layers.0.self_attn.k_proj.base_layer.weight.absmax\", \"base_model.model.model.layers.0.self_attn.k_proj.base_layer.weight.quant_map\", \"base_model.model.model.layers.0.self_attn.k_proj.base_layer.weight.quant_state.bitsandbytesnf4\", \"base_model.model.model.layers.0.self_attn.v_proj.base_layer.weight.absmax\", \"base_model.model.model.layers.0.self_attn.v_proj.base_layer.weight.quant_map\", \"base_model.model.model.layers.0.self_attn.v_proj.base_layer.weight.quant_state.bitsandbytesnf4\", \"base_model.model.model.layers.0.self_attn.o_proj.weight.absmax\", \"base_model.model.model.layers.0.self_attn.o_proj.weight.quant_map\", \"base_model.model.model.layers.0.self_attn.o_proj.weight.quant_state.bitsandbytes__nf4\", \"base_model.model.model.layers.0.mlp.gate_proj.base_layer.weight.absmax\", \"base_model.model.model.layers.0.mlp.gate_proj.base_layer.weight.quant_map\", \"base_model.model.model.layers.0.mlp.gate_proj.base_layer.weight.quant_state.bitsandbytesnf4\", \"base_model.model.model.layers.0.mlp.up_proj.base_layer.weight.absmax\", \"base_model.model.model.layers.0.mlp.up_proj.base_layer.weight.quant_map\", \"base_model.model.model.layers.0.mlp.up_proj.base_layer.weight.quant_state.bitsandbytesnf4\", \"base_model.model.model.layers.0.mlp.down_proj.base_layer.weight.absmax\", \"base_model.model.model.layers.0.mlp.down_proj.base_layer.weight.quant_map\", \"base_model.model.model.layers.0.mlp.down_proj.base_layer.weight.quant_state.bitsandbytesnf4\", \"base_model.model.model.layers.1.self_attn.q_proj.base_layer.weight.absmax\", \"base_model.model.model.layers.1.self_attn.q_proj.base_layer.weight.quant_map\", \"base_model.model.model.layers.1.self_attn.q_proj.base_layer.weight.quant_state.bitsandbytesnf4\", \"base_model.model.model.layers.1.self_attn.k_proj.base_layer.weight.absmax\", \"base_model.model.model.layers.1.self_attn.k_proj.base_layer.weight.quant_map\", \"base_model.model.model.layers.1.self_attn.k_proj.base_layer.weight.quant_state.bitsandbytesnf4\", \"base_model.model.model.layers.1.self_attn.v_proj.base_layer.weight.absmax\", \"base_model.model.model.layers.1.self_attn.v_proj.base_layer.weight.quant_map\", \"base_model.model.model.layers.1.self_attn.v_proj.base_layer.weight.quant_state.bitsandbytesnf4\", \"base_model.model.model.layers.1.self_attn.o_proj.weight.absmax\", \"base_model.model.model.layers.1.self_attn.o_proj.weight.quant_map\", \"base_model.model.model.layers.1.self_attn.o_proj.weight.quant_state.bitsandbytesnf4\", 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chwenjun225 commented 2 months ago

Oh, damn, I found the way, cause the model = get_peft_model(model, peft_config) we loaded at the absmax, quant_state, quant_state.bitsandbytes__nf4 so we need to remove these keys before load it in to model, here the solution:

new_sd = model.state_dict()

# Create a list to store keys to remove
keys_to_remove = []

for k in new_sd:
    if 'lora' in k:
        new_sd[k] = tensors[k]
    elif ('.absmax' in k) or ('.quant_state.bitsandbytes__nf4' in k) or ('.quant_map' in k): 
        keys_to_remove.append(k)
    else:
        continue

# Iterate over the list of keys to remove and delete them from the dictionary
for k in keys_to_remove:
    del new_sd[k]

model.load_state_dict(new_sd)