UnifiedForCausalLM(
  (model): UnifiedModel(
    (embed_tokens): Embedding(100289, 2048, padding_idx=100277)
    (layers): ModuleList(
      (0-15): 16 x Olmo2DecoderLayer(
        (self_attn): Olmo2Attention(
          (q_proj): Linear(in_features=2048, out_features=2048, bias=False)
          (k_proj): Linear(in_features=2048, out_features=2048, bias=False)
          (v_proj): Linear(in_features=2048, out_features=2048, bias=False)
          (o_proj): Linear(in_features=2048, out_features=2048, bias=False)
          (q_norm): Olmo2RMSNorm((2048,), eps=1e-06)
          (k_norm): Olmo2RMSNorm((2048,), eps=1e-06)
        )
        (mlp): Olmo2MLP(
          (gate_proj): Linear(in_features=2048, out_features=8192, bias=False)
          (up_proj): Linear(in_features=2048, out_features=8192, bias=False)
          (down_proj): Linear(in_features=8192, out_features=2048, bias=False)
          (act_fn): SiLU()
        )
        (post_attention_layernorm): Olmo2RMSNorm((2048,), eps=1e-06)
        (post_feedforward_layernorm): Olmo2RMSNorm((2048,), eps=1e-06)
      )
    )
    (norm): Olmo2RMSNorm((2048,), eps=1e-06)
    (rotary_emb): Olmo2RotaryEmbedding()
    (visual_encoder): MultiPathCLIPVisionTower(
      (slow_vision_tower): ConvNextVisionTower(
        (vision_tower): ConvNeXt(
          (stem): Sequential(
            (0): Conv2d(3, 192, kernel_size=(4, 4), stride=(4, 4))
            (1): LayerNorm2d((192,), eps=1e-06, elementwise_affine=True)
          )
          (stages): Sequential(
            (0): ConvNeXtStage(
              (downsample): Identity()
              (blocks): Sequential(
                (0): ConvNeXtBlock(
                  (conv_dw): Conv2d(192, 192, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=192)
                  (norm): LayerNorm((192,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=192, out_features=768, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=768, out_features=192, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (1): ConvNeXtBlock(
                  (conv_dw): Conv2d(192, 192, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=192)
                  (norm): LayerNorm((192,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=192, out_features=768, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=768, out_features=192, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (2): ConvNeXtBlock(
                  (conv_dw): Conv2d(192, 192, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=192)
                  (norm): LayerNorm((192,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=192, out_features=768, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=768, out_features=192, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
              )
            )
            (1): ConvNeXtStage(
              (downsample): Sequential(
                (0): LayerNorm2d((192,), eps=1e-06, elementwise_affine=True)
                (1): Conv2d(192, 384, kernel_size=(2, 2), stride=(2, 2))
              )
              (blocks): Sequential(
                (0): ConvNeXtBlock(
                  (conv_dw): Conv2d(384, 384, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=384)
                  (norm): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=384, out_features=1536, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=1536, out_features=384, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (1): ConvNeXtBlock(
                  (conv_dw): Conv2d(384, 384, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=384)
                  (norm): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=384, out_features=1536, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=1536, out_features=384, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (2): ConvNeXtBlock(
                  (conv_dw): Conv2d(384, 384, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=384)
                  (norm): LayerNorm((384,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=384, out_features=1536, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=1536, out_features=384, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
              )
            )
            (2): ConvNeXtStage(
              (downsample): Sequential(
                (0): LayerNorm2d((384,), eps=1e-06, elementwise_affine=True)
                (1): Conv2d(384, 768, kernel_size=(2, 2), stride=(2, 2))
              )
              (blocks): Sequential(
                (0): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (1): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (2): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (3): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (4): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (5): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (6): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (7): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (8): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (9): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (10): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (11): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (12): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (13): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (14): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (15): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (16): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (17): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (18): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (19): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (20): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (21): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (22): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (23): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (24): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (25): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (26): ConvNeXtBlock(
                  (conv_dw): Conv2d(768, 768, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=768)
                  (norm): LayerNorm((768,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=768, out_features=3072, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=3072, out_features=768, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
              )
            )
            (3): ConvNeXtStage(
              (downsample): Sequential(
                (0): LayerNorm2d((768,), eps=1e-06, elementwise_affine=True)
                (1): Conv2d(768, 1536, kernel_size=(2, 2), stride=(2, 2))
              )
              (blocks): Sequential(
                (0): ConvNeXtBlock(
                  (conv_dw): Conv2d(1536, 1536, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=1536)
                  (norm): LayerNorm((1536,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=1536, out_features=6144, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=6144, out_features=1536, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (1): ConvNeXtBlock(
                  (conv_dw): Conv2d(1536, 1536, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=1536)
                  (norm): LayerNorm((1536,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=1536, out_features=6144, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=6144, out_features=1536, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
                (2): ConvNeXtBlock(
                  (conv_dw): Conv2d(1536, 1536, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=1536)
                  (norm): LayerNorm((1536,), eps=1e-06, elementwise_affine=True)
                  (mlp): Mlp(
                    (fc1): Linear(in_features=1536, out_features=6144, bias=True)
                    (act): GELU()
                    (drop1): Dropout(p=0.0, inplace=False)
                    (norm): Identity()
                    (fc2): Linear(in_features=6144, out_features=1536, bias=True)
                    (drop2): Dropout(p=0.0, inplace=False)
                  )
                  (shortcut): Identity()
                  (drop_path): Identity()
                )
              )
            )
          )
          (norm_pre): Identity()
          (head): NormMlpClassifierHead(
            (global_pool): SelectAdaptivePool2d(pool_type=avg, flatten=Identity())
            (norm): LayerNorm2d((1536,), eps=1e-06, elementwise_affine=True)
            (flatten): Flatten(start_dim=1, end_dim=-1)
            (pre_logits): Sequential(
              (fc): Linear(in_features=1536, out_features=1536, bias=True)
              (act): GELU()
            )
            (drop): Dropout(p=0.0, inplace=False)
            (fc): Linear(in_features=1536, out_features=1000, bias=True)
          )
        )
      )
      (fast_vision_tower): CLIPVisionTower(
        (vision_tower): CLIPVisionModel(
          (vision_model): CLIPVisionTransformer(
            (embeddings): CLIPVisionEmbeddings(
              (patch_embedding): Conv2d(3, 1024, kernel_size=(14, 14), stride=(14, 14), bias=False)
              (position_embedding): Embedding(577, 1024)
            )
            (pre_layrnorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
            (encoder): CLIPEncoder(
              (layers): ModuleList(
                (0-23): 24 x CLIPEncoderLayer(
                  (self_attn): CLIPSdpaAttention(
                    (k_proj): Linear(in_features=1024, out_features=1024, bias=True)
                    (v_proj): Linear(in_features=1024, out_features=1024, bias=True)
                    (q_proj): Linear(in_features=1024, out_features=1024, bias=True)
                    (out_proj): Linear(in_features=1024, out_features=1024, bias=True)
                  )
                  (layer_norm1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
                  (mlp): CLIPMLP(
                    (activation_fn): QuickGELUActivation()
                    (fc1): Linear(in_features=1024, out_features=4096, bias=True)
                    (fc2): Linear(in_features=4096, out_features=1024, bias=True)
                  )
                  (layer_norm2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
                )
              )
            )
            (post_layernorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
          )
        )
      )
      (align_stages_latent): ModuleList(
        (0-2): 3 x S2FStitchAlignModuleV2(
          (slow_conv): Conv2d(1536, 1536, kernel_size=(1, 1), stride=(1, 1))
          (slow_proj): Conv2d(1536, 1024, kernel_size=(1, 1), stride=(1, 1))
          (fast_conv): Conv2d(1024, 1024, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3), groups=1024)
          (fast_proj): Conv2d(1024, 1024, kernel_size=(1, 1), stride=(1, 1))
          (gate): Sequential(
            (0): Linear(in_features=2048, out_features=512, bias=True)
            (1): GELU(approximate='none')
            (2): Linear(in_features=512, out_features=1, bias=True)
          )
        )
      )
      (align_stages): ModuleList(
        (0): MultiPathAlignModule(
          (fast_proj): Linear(in_features=1024, out_features=1024, bias=True)
          (slow_proj): Linear(in_features=1536, out_features=1024, bias=True)
        )
      )
    )
    (vl_projector): Sequential(
      (0): Linear(in_features=1024, out_features=2048, bias=True)
      (1): GELU(approximate='none')
      (2): Linear(in_features=2048, out_features=2048, bias=True)
    )
  )
  (lm_head): Linear(in_features=2048, out_features=100289, bias=False)
)