model_architecture.txt

PeftModelForCausalLM(
  (base_model): LoraModel(
    (model): LlamaForCausalLM(
      (model): LlamaModel(
        (embed_tokens): Embedding(128256, 4096)
        (layers): ModuleList(
          (0-31): 32 x LlamaDecoderLayer(
            (self_attn): LlamaAttention(
              (q_proj): lora.Linear4bit(
                (base_layer): Linear4bit(in_features=4096, out_features=4096, bias=False)
                (lora_dropout): ModuleDict(
                  (default): Identity()
                )
                (lora_A): ModuleDict(
                  (default): Linear(in_features=4096, out_features=16, bias=False)
                )
                (lora_B): ModuleDict(
                  (default): Linear(in_features=16, out_features=4096, bias=False)
                )
                (lora_embedding_A): ParameterDict()
                (lora_embedding_B): ParameterDict()
                (lora_magnitude_vector): ModuleDict()
              )
              (k_proj): lora.Linear4bit(
                (base_layer): Linear4bit(in_features=4096, out_features=1024, bias=False)
                (lora_dropout): ModuleDict(
                  (default): Identity()
                )
                (lora_A): ModuleDict(
                  (default): Linear(in_features=4096, out_features=16, bias=False)
                )
                (lora_B): ModuleDict(
                  (default): Linear(in_features=16, out_features=1024, bias=False)
                )
                (lora_embedding_A): ParameterDict()
                (lora_embedding_B): ParameterDict()
                (lora_magnitude_vector): ModuleDict()
              )
              (v_proj): lora.Linear4bit(
                (base_layer): Linear4bit(in_features=4096, out_features=1024, bias=False)
                (lora_dropout): ModuleDict(
                  (default): Identity()
                )
                (lora_A): ModuleDict(
                  (default): Linear(in_features=4096, out_features=16, bias=False)
                )
                (lora_B): ModuleDict(
                  (default): Linear(in_features=16, out_features=1024, bias=False)
                )
                (lora_embedding_A): ParameterDict()
                (lora_embedding_B): ParameterDict()
                (lora_magnitude_vector): ModuleDict()
              )
              (o_proj): lora.Linear4bit(
                (base_layer): Linear4bit(in_features=4096, out_features=4096, bias=False)
                (lora_dropout): ModuleDict(
                  (default): Identity()
                )
                (lora_A): ModuleDict(
                  (default): Linear(in_features=4096, out_features=16, bias=False)
                )
                (lora_B): ModuleDict(
                  (default): Linear(in_features=16, out_features=4096, bias=False)
                )
                (lora_embedding_A): ParameterDict()
                (lora_embedding_B): ParameterDict()
                (lora_magnitude_vector): ModuleDict()
              )
              (rotary_emb): LlamaExtendedRotaryEmbedding()
            )
            (mlp): LlamaMLP(
              (gate_proj): lora.Linear4bit(
                (base_layer): Linear4bit(in_features=4096, out_features=14336, bias=False)
                (lora_dropout): ModuleDict(
                  (default): Identity()
                )
                (lora_A): ModuleDict(
                  (default): Linear(in_features=4096, out_features=16, bias=False)
                )
                (lora_B): ModuleDict(
                  (default): Linear(in_features=16, out_features=14336, bias=False)
                )
                (lora_embedding_A): ParameterDict()
                (lora_embedding_B): ParameterDict()
                (lora_magnitude_vector): ModuleDict()
              )
              (up_proj): lora.Linear4bit(
                (base_layer): Linear4bit(in_features=4096, out_features=14336, bias=False)
                (lora_dropout): ModuleDict(
                  (default): Identity()
                )
                (lora_A): ModuleDict(
                  (default): Linear(in_features=4096, out_features=16, bias=False)
                )
                (lora_B): ModuleDict(
                  (default): Linear(in_features=16, out_features=14336, bias=False)
                )
                (lora_embedding_A): ParameterDict()
                (lora_embedding_B): ParameterDict()
                (lora_magnitude_vector): ModuleDict()
              )
              (down_proj): lora.Linear4bit(
                (base_layer): Linear4bit(in_features=14336, out_features=4096, bias=False)
                (lora_dropout): ModuleDict(
                  (default): Identity()
                )
                (lora_A): ModuleDict(
                  (default): Linear(in_features=14336, out_features=16, bias=False)
                )
                (lora_B): ModuleDict(
                  (default): Linear(in_features=16, out_features=4096, bias=False)
                )
                (lora_embedding_A): ParameterDict()
                (lora_embedding_B): ParameterDict()
                (lora_magnitude_vector): ModuleDict()
              )
              (act_fn): SiLU()
            )
            (input_layernorm): LlamaRMSNorm((4096,), eps=1e-05)
            (post_attention_layernorm): LlamaRMSNorm((4096,), eps=1e-05)
          )
        )
        (norm): LlamaRMSNorm((4096,), eps=1e-05)
        (rotary_emb): LlamaRotaryEmbedding()
      )
      (lm_head): Linear(in_features=4096, out_features=128256, bias=False)
    )
  )
)