mini-glm-5.2-fp8 / config.json
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{
"architectures": [
"GlmMoeDsaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"dtype": "bfloat16",
"eos_token_id": [
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"ep_size": 1,
"first_k_dense_replace": 2,
"head_dim": 64,
"hidden_act": "silu",
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"index_head_dim": 128,
"index_n_heads": 32,
"index_share_for_mtp_iteration": true,
"index_skip_topk_offset": 3,
"index_topk": 2048,
"index_topk_freq": 4,
"index_topk_pattern": null,
"indexer_rope_interleave": true,
"indexer_types": [
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"shared",
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"full"
],
"initializer_range": 0.02,
"intermediate_size": 12288,
"kv_lora_rank": 512,
"max_position_embeddings": 16384,
"mlp_layer_types": [
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"sparse",
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"sparse",
"sparse",
"sparse",
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"sparse"
],
"model_type": "glm_moe_dsa",
"moe_intermediate_size": 2048,
"moe_layer_freq": 1,
"n_group": 1,
"n_routed_experts": 256,
"n_shared_experts": 1,
"norm_topk_prob": true,
"num_attention_heads": 64,
"num_experts_per_tok": 8,
"num_hidden_layers": 14,
"num_key_value_heads": 64,
"num_nextn_predict_layers": 1,
"pad_token_id": 154820,
"pretraining_tp": 1,
"q_lora_rank": 2048,
"qk_head_dim": 256,
"qk_nope_head_dim": 192,
"qk_rope_head_dim": 64,
"quantization_config": {
"activation_scheme": "dynamic",
"fmt": "e4m3",
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"quant_method": "fp8",
"weight_block_size": [
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]
},
"rms_norm_eps": 1e-05,
"rope_interleave": true,
"rope_parameters": {
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"rope_type": "default"
},
"routed_scaling_factor": 2.5,
"scoring_func": "sigmoid",
"tie_word_embeddings": false,
"topk_group": 1,
"topk_method": "noaux_tc",
"torch_dtype": "bfloat16",
"transformers_version": "5.12.0",
"use_cache": true,
"v1c_full_upscale": {
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"active_hidden_size": 1024,
"active_routed_experts": 16,
"expansion_strategy": "tiled active subspace with averaged input repeats",
"inactive_expert_bias": -1000000000.0,
"mtp_source_checkpoint": "/root/inference-v2/mini-glm-5.2/v1b-mtp/checkpoints/mtp-active-decoder-serveddata-align-1k/final",
"num_nextn_predict_layers": 1,
"source_checkpoint": "/root/inference-v2/mini-glm-5.2/v1a-mini-model/checkpoints/stage-b2-finewebedu16k-cont100m-2gpu/final",
"strict_equivalence_caveat": "RoPE 32->64 maps source frequencies into every-other target pair; unused target RoPE pairs are zero.",
"target_config": "/root/inference-v2/mini-glm-5.2/v1a-mini-model/config/glm-5.2-original-config.json"
},
"v_head_dim": 256,
"vocab_size": 154880
}