attractor-140m / config.json
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Update config.json
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{
"name": "eqlm-small-140m",
"hf_config": {
"name": "eqlm-small-140m"
},
"block_size": 2048,
"n_embd": 1024,
"intermediate_size": 4096,
"num_attention_heads": 8,
"num_key_value_heads": 8,
"vocab_size": 32768,
"padding_multiple": 64,
"padded_vocab_size": 32768,
"rope_settings": {
"use_rope": true,
"rope_condense_ratio": 1,
"rope_base": 50000
},
"use_abacus": false,
"randomize_positions_from": null,
"block_class_name": "TransformerPreNormBlock",
"norm_class_name": "RMSNorm",
"attn_impl": "flash",
"norm_eps": 1e-05,
"mlp_class_name": "BaseMLP",
"nonlin_name": "ReLU2",
"bias": false,
"qk_bias": false,
"init_strategy": "scaled-zero",
"init_orthogonal": true,
"skip_initialization": false,
"mup_model_scaling_factor": 1,
"use_fused_head": "pytorch",
"debias_attention": false,
"center_attention": false,
"clip_qkv": null,
"qk_norm": true,
"logit_softcap": null,
"causal": true,
"activation_checkpoint_impl": "per-block",
"simple_ops": false,
"strategy": "ddp",
"n_backbone_layers": 7,
"n_fp_blocks": 1,
"tie_embeddings": true,
"solver": "anderson",
"max_iter": 64,
"min_iter": 6,
"tol": 0.0003,
"anderson_m": 5,
"anderson_beta": 1.0,
"backward_type": "onestep",
"backward_max_iter": 64,
"backward_min_iter": 6,
"backward_tol": 0.0003,
"adjoint_grad_clip": null,
"layer_scale_init": 0.75,
"gamma_max": 0.75,
"fp_lr_scale": 0.5,
"fp_wd": 0.1,
"recurrent_embedding_dimension": 1024,
"model_class_name": "EQLM",
"_class_name": "EQLMConfig"
}