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gptj_arch.txt
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gptj_arch.txt
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GPTJModel(
(wte): Embedding(50400, 4096)
(drop): Dropout(p=0.0, inplace=False)
(h): ModuleList(
(0): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(1): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(2): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(3): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(4): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(5): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(6): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(7): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(8): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(9): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(10): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(11): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(12): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(13): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(14): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(15): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(16): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(17): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(18): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(19): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(20): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(21): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(22): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(23): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(24): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(25): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(26): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
(27): GPTJBlock(
(ln_1): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
(attn): GPTJAttention(
(attn_dropout): Dropout(p=0.0, inplace=False)
(resid_dropout): Dropout(p=0.0, inplace=False)
(k_proj): Linear(in_features=4096, out_features=4096, bias=False)
(v_proj): Linear(in_features=4096, out_features=4096, bias=False)
(q_proj): Linear(in_features=4096, out_features=4096, bias=False)
(out_proj): Linear(in_features=4096, out_features=4096, bias=False)
)
(mlp): GPTJMLP(
(fc_in): Linear(in_features=4096, out_features=16384, bias=True)
(fc_out): Linear(in_features=16384, out_features=4096, bias=True)
(dropout): Dropout(p=0.0, inplace=False)
)
)
)
(ln_f): LayerNorm((4096,), eps=1e-05, elementwise_affine=True)
)