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19 lines
1.4 KiB
JSON
19 lines
1.4 KiB
JSON
{
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"name_map": {
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"text_model.embeddings.token_embedding": "Sum.TokenEncoder",
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"text_model.embeddings.position_embedding": "Sum.PositionalEncoder.Embedding",
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"text_model.final_layer_norm": "LayerNorm",
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"text_projection": "Linear"
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},
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"regex_map": {
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"text_model\\.encoder\\.layers\\.(?P<layer>\\d+)\\.layer_norm(?P<norm>\\d+)": "TransformerLayer_{int(layer) + 1}.Residual_{norm}.LayerNorm",
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"text_model\\.encoder\\.layers\\.(?P<layer_number>\\d+)\\.self_attn\\.q_proj": "TransformerLayer_{int(layer_number) + 1}.Residual_1.SelfAttention.Distribute.Linear_1",
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"text_model\\.encoder\\.layers\\.(?P<layer_number>\\d+)\\.self_attn\\.k_proj": "TransformerLayer_{int(layer_number) + 1}.Residual_1.SelfAttention.Distribute.Linear_2",
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"text_model\\.encoder\\.layers\\.(?P<layer_number>\\d+)\\.self_attn\\.v_proj": "TransformerLayer_{int(layer_number) + 1}.Residual_1.SelfAttention.Distribute.Linear_3",
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"text_model\\.encoder\\.layers\\.(?P<layer_number>\\d+)\\.self_attn\\.out_proj": "TransformerLayer_{int(layer_number) + 1}.Residual_1.SelfAttention.Linear",
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"text_model\\.encoder\\.layers\\.(?P<layer_number>\\d+)\\.mlp\\.fc(?P<fc_num>\\d+)": "TransformerLayer_{int(layer_number) + 1}.Residual_2.FeedForward.Linear_{fc_num}"
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},
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"ignore_prefixes": [],
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"source_aliases": {},
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"reshapes": {}
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} |