lenepa-cauker2m-5000-patchnorm-d256 / lenepa_encoder_config.json
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LeNEPA trained on a custom CauKer-2M dataset with 5000 points per series
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{
"bias": true,
"channel_size": 5000,
"channels": [
"c0"
],
"depth": 8,
"dim": 256,
"format": "lenepa_encoder",
"format_version": 1,
"is_causal": true,
"mlp_ratio": 4.0,
"nepa_final_norm": "ln",
"nepa_patch_embed_cnn_dim": 192,
"nepa_patch_embed_scalar_epsilon": 1.1,
"nepa_patch_embed_scalar_hidden_dim": 32,
"nepa_patch_embed_scalar_scales": [
0.0001,
0.001,
0.01,
0.1,
1.0,
10.0,
100.0,
1000.0,
10000.0
],
"nepa_patch_embed_scalar_stats_mode": "patch_norm",
"nepa_rep_pooling": "mean",
"nepa_static_tokenizer": "conv_patch_embed",
"norm_eps": 1e-06,
"num_heads": 4,
"num_patches": 625,
"num_registers": 0,
"patch_size": 8,
"pos_embed_type": "none",
"qk_norm_eps": 1e-06,
"qkv_bias": true,
"rope_base": 10000,
"sampling_frequency": 1,
"use_nepa": true,
"use_qk_norm": true,
"use_rope": true,
"use_swiglu": true
}