nvidia/MiniMax-M2.5-NVFP4
38122k
1{2 "architectures": [3 "MiniMaxM2ForCausalLM"4 ],5 "attention_dropout": 0.0,6 "attn_type_list": [7 1,8 1,9 1,10 1,11 1,12 1,13 1,14 1,15 1,16 1,17 1,18 1,19 1,20 1,21 1,22 1,23 1,24 1,25 1,26 1,27 1,28 1,29 1,30 1,31 1,32 1,33 1,34 1,35 1,36 1,37 1,38 1,39 1,40 1,41 1,42 1,43 1,44 1,45 1,46 1,47 1,48 1,49 1,50 1,51 1,52 1,53 1,54 1,55 1,56 1,57 1,58 1,59 1,60 1,61 1,62 1,63 1,64 1,65 1,66 1,67 1,68 169 ],70 "auto_map": {71 "AutoConfig": "configuration_minimax_m2.MiniMaxM2Config",72 "AutoModelForCausalLM": "modeling_minimax_m2.MiniMaxM2ForCausalLM"73 },74 "bos_token_id": 1,75 "dtype": "bfloat16",76 "eos_token_id": 2,77 "head_dim": 128,78 "hidden_act": "silu",79 "hidden_size": 3072,80 "initializer_range": 0.02,81 "intermediate_size": 1536,82 "max_position_embeddings": 196608,83 "model_type": "minimax_m2",84 "mtp_transformer_layers": 1,85 "num_attention_heads": 48,86 "num_experts_per_tok": 8,87 "num_hidden_layers": 62,88 "num_key_value_heads": 8,89 "num_local_experts": 256,90 "num_mtp_modules": 3,91 "output_router_logits": false,92 "partial_rotary_factor": 0.5,93 "qk_norm_type": "per_layer",94 "quantization_config": {95 "config_groups": {96 "group_0": {97 "input_activations": {98 "dynamic": false,99 "num_bits": 4,100 "type": "float",101 "group_size": 16102 },103 "weights": {104 "dynamic": false,105 "num_bits": 4,106 "type": "float",107 "group_size": 16108 },109 "targets": [110 "Linear"111 ]112 }113 },114 "ignore": [115 "lm_head",116 "model.layers.0.block_sparse_moe.gate",117 "model.layers.0.self_attn*",118 "model.layers.1.block_sparse_moe.gate",119 "model.layers.1.self_attn*",120 "model.layers.10.block_sparse_moe.gate",121 "model.layers.10.self_attn*",122 "model.layers.11.block_sparse_moe.gate",123 "model.layers.11.self_attn*",124 "model.layers.12.block_sparse_moe.gate",125 "model.layers.12.self_attn*",126 "model.layers.13.block_sparse_moe.gate",127 "model.layers.13.self_attn*",128 "model.layers.14.block_sparse_moe.gate",129 "model.layers.14.self_attn*",130 "model.layers.15.block_sparse_moe.gate",131 "model.layers.15.self_attn*",132 "model.layers.16.block_sparse_moe.gate",133 "model.layers.16.self_attn*",134 "model.layers.17.block_sparse_moe.gate",135 "model.layers.17.self_attn*",136 "model.layers.18.block_sparse_moe.gate",137 "model.layers.18.self_attn*",138 "model.layers.19.block_sparse_moe.gate",139 "model.layers.19.self_attn*",140 "model.layers.2.block_sparse_moe.gate",141 "model.layers.2.self_attn*",142 "model.layers.20.block_sparse_moe.gate",143 "model.layers.20.self_attn*",144 "model.layers.21.block_sparse_moe.gate",145 "model.layers.21.self_attn*",146 "model.layers.22.block_sparse_moe.gate",147 "model.layers.22.self_attn*",148 "model.layers.23.block_sparse_moe.gate",149 "model.layers.23.self_attn*",150 "model.layers.24.block_sparse_moe.gate",151 "model.layers.24.self_attn*",152 "model.layers.25.block_sparse_moe.gate",153 "model.layers.25.self_attn*",154 "model.layers.26.block_sparse_moe.gate",155 "model.layers.26.self_attn*",156 "model.layers.27.block_sparse_moe.gate",157 "model.layers.27.self_attn*",158 "model.layers.28.block_sparse_moe.gate",159 "model.layers.28.self_attn*",160 "model.layers.29.block_sparse_moe.gate",161 "model.layers.29.self_attn*",162 "model.layers.3.block_sparse_moe.gate",163 "model.layers.3.self_attn*",164 "model.layers.30.block_sparse_moe.gate",165 "model.layers.30.self_attn*",166 "model.layers.31.block_sparse_moe.gate",167 "model.layers.31.self_attn*",168 "model.layers.32.block_sparse_moe.gate",169 "model.layers.32.self_attn*",170 "model.layers.33.block_sparse_moe.gate",171 "model.layers.33.self_attn*",172 "model.layers.34.block_sparse_moe.gate",173 "model.layers.34.self_attn*",174 "model.layers.35.block_sparse_moe.gate",175 "model.layers.35.self_attn*",176 "model.layers.36.block_sparse_moe.gate",177 "model.layers.36.self_attn*",178 "model.layers.37.block_sparse_moe.gate",179 "model.layers.37.self_attn*",180 "model.layers.38.block_sparse_moe.gate",181 "model.layers.38.self_attn*",182 "model.layers.39.block_sparse_moe.gate",183 "model.layers.39.self_attn*",184 "model.layers.4.block_sparse_moe.gate",185 "model.layers.4.self_attn*",186 "model.layers.40.block_sparse_moe.gate",187 "model.layers.40.self_attn*",188 "model.layers.41.block_sparse_moe.gate",189 "model.layers.41.self_attn*",190 "model.layers.42.block_sparse_moe.gate",191 "model.layers.42.self_attn*",192 "model.layers.43.block_sparse_moe.gate",193 "model.layers.43.self_attn*",194 "model.layers.44.block_sparse_moe.gate",195 "model.layers.44.self_attn*",196 "model.layers.45.block_sparse_moe.gate",197 "model.layers.45.self_attn*",198 "model.layers.46.block_sparse_moe.gate",199 "model.layers.46.self_attn*",200 "model.layers.47.block_sparse_moe.gate",201 "model.layers.47.self_attn*",202 "model.layers.48.block_sparse_moe.gate",203 "model.layers.48.self_attn*",204 "model.layers.49.block_sparse_moe.gate",205 "model.layers.49.self_attn*",206 "model.layers.5.block_sparse_moe.gate",207 "model.layers.5.self_attn*",208 "model.layers.50.block_sparse_moe.gate",209 "model.layers.50.self_attn*",210 "model.layers.51.block_sparse_moe.gate",211 "model.layers.51.self_attn*",212 "model.layers.52.block_sparse_moe.gate",213 "model.layers.52.self_attn*",214 "model.layers.53.block_sparse_moe.gate",215 "model.layers.53.self_attn*",216 "model.layers.54.block_sparse_moe.gate",217 "model.layers.54.self_attn*",218 "model.layers.55.block_sparse_moe.gate",219 "model.layers.55.self_attn*",220 "model.layers.56.block_sparse_moe.gate",221 "model.layers.56.self_attn*",222 "model.layers.57.block_sparse_moe.gate",223 "model.layers.57.self_attn*",224 "model.layers.58.block_sparse_moe.gate",225 "model.layers.58.self_attn*",226 "model.layers.59.block_sparse_moe.gate",227 "model.layers.59.self_attn*",228 "model.layers.6.block_sparse_moe.gate",229 "model.layers.6.self_attn*",230 "model.layers.60.block_sparse_moe.gate",231 "model.layers.60.self_attn*",232 "model.layers.61.block_sparse_moe.gate",233 "model.layers.61.self_attn*",234 "model.layers.7.block_sparse_moe.gate",235 "model.layers.7.self_attn*",236 "model.layers.8.block_sparse_moe.gate",237 "model.layers.8.self_attn*",238 "model.layers.9.block_sparse_moe.gate",239 "model.layers.9.self_attn*"240 ],241 "quant_algo": "NVFP4",242 "kv_cache_scheme": {243 "dynamic": false,244 "num_bits": 8,245 "type": "float"246 },247 "producer": {248 "name": "modelopt",249 "version": "0.0.1.dev507+gbb6639d33"250 },251 "quant_method": "modelopt"252 },253 "rms_norm_eps": 1e-06,254 "rope_theta": 5000000,255 "rotary_dim": 64,256 "router_aux_loss_coef": 0.001,257 "router_jitter_noise": 0.0,258 "scoring_func": "sigmoid",259 "shared_intermediate_size": 0,260 "sliding_window": null,261 "tie_word_embeddings": false,262 "transformers_version": "4.57.1",263 "use_cache": true,264 "use_mtp": true,265 "use_qk_norm": true,266 "use_routing_bias": true,267 "vocab_size": 200064,268 "sparse_attention_config": {269 "config_groups": {270 "group_0": {271 "sparse_algo": "softmax_skip",272 "targets": [273 "MiniMaxM2Attention"274 ]275 }276 },277 "threshold_scale_factor": {278 "formula": "a * exp(b * target_sparsity)",279 "prefill": {280 "a": 87.239981,281 "b": 5.3221282 },283 "decode": {284 "a": 0.032140,285 "b": 11.7877286 }287 },288 "producer": {289 "name": "modelopt",290 "version": "0.43.0.dev27+g26aa1d0b1"291 }292 }293}294 