Former-commit-id: aa7d104f8e050d12cb8f585bc8a52c850995500f
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@@ -24,10 +24,10 @@ class FinetuningArguments:
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default="mlp",
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metadata={"help": "Name of trainable modules for partial-parameter (freeze) fine-tuning. \
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LLaMA choices: [\"mlp\", \"self_attn\"], \
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BLOOM & Falcon & ChatGLM2 choices: [\"mlp\", \"self_attention\"], \
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BLOOM & Falcon & ChatGLM choices: [\"mlp\", \"self_attention\"], \
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Qwen choices: [\"mlp\", \"attn\"], \
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Phi-1.5 choices: [\"mlp\", \"mixer\"], \
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LLaMA-2, Baichuan, InternLM, XVERSE choices: the same as LLaMA."}
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LLaMA-2, BlueLM, Baichuan, InternLM, Mistral, Skywork, XVERSE, Yi choices: the same as LLaMA."}
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)
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lora_rank: Optional[int] = field(
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default=8,
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@@ -45,11 +45,11 @@ class FinetuningArguments:
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default=None,
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metadata={"help": "Name(s) of target modules to apply LoRA. Use commas to separate multiple modules. \
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LLaMA choices: [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\", \"gate_proj\", \"up_proj\", \"down_proj\"], \
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BLOOM & Falcon & ChatGLM2 choices: [\"query_key_value\", \"self_attention.dense\", \"mlp.dense\"], \
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BLOOM & Falcon & ChatGLM choices: [\"query_key_value\", \"self_attention.dense\", \"mlp.dense\"], \
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Baichuan choices: [\"W_pack\", \"o_proj\", \"gate_proj\", \"up_proj\", \"down_proj\"], \
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Qwen choices: [\"c_attn\", \"attn.c_proj\", \"w1\", \"w2\", \"mlp.c_proj\"], \
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Phi-1.5 choices: [\"Wqkv\", \"out_proj\", \"fc1\", \"fc2\"], \
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LLaMA-2, InternLM, XVERSE choices: the same as LLaMA."}
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LLaMA-2, BlueLM, InternLM, Mistral, Skywork, XVERSE, Yi choices: the same as LLaMA."}
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)
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additional_target: Optional[str] = field(
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default=None,
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