Instructions to use RedHatAI/Qwen3.6-27B-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RedHatAI/Qwen3.6-27B-FP8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="RedHatAI/Qwen3.6-27B-FP8") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("RedHatAI/Qwen3.6-27B-FP8") model = AutoModelForImageTextToText.from_pretrained("RedHatAI/Qwen3.6-27B-FP8") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use RedHatAI/Qwen3.6-27B-FP8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "RedHatAI/Qwen3.6-27B-FP8" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RedHatAI/Qwen3.6-27B-FP8", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/RedHatAI/Qwen3.6-27B-FP8
- SGLang
How to use RedHatAI/Qwen3.6-27B-FP8 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "RedHatAI/Qwen3.6-27B-FP8" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RedHatAI/Qwen3.6-27B-FP8", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "RedHatAI/Qwen3.6-27B-FP8" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RedHatAI/Qwen3.6-27B-FP8", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use RedHatAI/Qwen3.6-27B-FP8 with Docker Model Runner:
docker model run hf.co/RedHatAI/Qwen3.6-27B-FP8
File size: 51,346 Bytes
b870275 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 | {
"architectures": [
"Qwen3_5ForConditionalGeneration"
],
"image_token_id": 248056,
"language_model_only": false,
"model_type": "qwen3_5",
"text_config": {
"attention_bias": false,
"attention_dropout": 0.0,
"attn_output_gate": true,
"bos_token_id": 248044,
"dtype": "bfloat16",
"eos_token_id": 248044,
"full_attention_interval": 4,
"head_dim": 256,
"hidden_act": "silu",
"hidden_size": 5120,
"initializer_range": 0.02,
"intermediate_size": 17408,
"layer_types": [
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention",
"linear_attention",
"linear_attention",
"linear_attention",
"full_attention"
],
"linear_conv_kernel_dim": 4,
"linear_key_head_dim": 128,
"linear_num_key_heads": 16,
"linear_num_value_heads": 48,
"linear_value_head_dim": 128,
"mamba_ssm_dtype": "float32",
"max_position_embeddings": 262144,
"model_type": "qwen3_5_text",
"mtp_num_hidden_layers": 1,
"mtp_use_dedicated_embeddings": false,
"num_attention_heads": 24,
"num_hidden_layers": 64,
"num_key_value_heads": 4,
"output_gate_type": "swish",
"pad_token_id": null,
"partial_rotary_factor": 0.25,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"mrope_interleaved": true,
"mrope_section": [
11,
11,
10
],
"partial_rotary_factor": 0.25,
"rope_theta": 10000000,
"rope_type": "default"
},
"tie_word_embeddings": false,
"use_cache": true,
"vocab_size": 248320
},
"tie_word_embeddings": false,
"transformers_version": "4.57.1",
"video_token_id": 248057,
"vision_config": {
"deepstack_visual_indexes": [],
"depth": 27,
"hidden_act": "gelu_pytorch_tanh",
"hidden_size": 1152,
"in_channels": 3,
"initializer_range": 0.02,
"intermediate_size": 4304,
"model_type": "qwen3_5",
"num_heads": 16,
"num_position_embeddings": 2304,
"out_hidden_size": 5120,
"patch_size": 16,
"spatial_merge_size": 2,
"temporal_patch_size": 2
},
"vision_end_token_id": 248054,
"vision_start_token_id": 248053,
"quantization_config": {
"activation_scheme": "dynamic",
"fmt": "e4m3",
"quant_method": "fp8",
"modules_to_not_convert": [
"model.visual.blocks.0.attn.proj",
"model.visual.blocks.0.attn.qkv",
"model.visual.blocks.0.mlp.linear_fc1",
"model.visual.blocks.0.mlp.linear_fc2",
"visual.blocks.0.attn.proj",
"visual.blocks.0.attn.qkv_proj",
"visual.blocks.0.mlp.linear_fc1",
"visual.blocks.0.mlp.linear_fc2",
"model.visual.blocks.1.attn.proj",
"model.visual.blocks.1.attn.qkv",
"model.visual.blocks.1.mlp.linear_fc1",
"model.visual.blocks.1.mlp.linear_fc2",
"visual.blocks.1.attn.proj",
"visual.blocks.1.attn.qkv_proj",
"visual.blocks.1.mlp.linear_fc1",
"visual.blocks.1.mlp.linear_fc2",
"model.visual.blocks.2.attn.proj",
"model.visual.blocks.2.attn.qkv",
"model.visual.blocks.2.mlp.linear_fc1",
"model.visual.blocks.2.mlp.linear_fc2",
"visual.blocks.2.attn.proj",
"visual.blocks.2.attn.qkv_proj",
"visual.blocks.2.mlp.linear_fc1",
"visual.blocks.2.mlp.linear_fc2",
"model.visual.blocks.3.attn.proj",
"model.visual.blocks.3.attn.qkv",
"model.visual.blocks.3.mlp.linear_fc1",
"model.visual.blocks.3.mlp.linear_fc2",
"visual.blocks.3.attn.proj",
"visual.blocks.3.attn.qkv_proj",
"visual.blocks.3.mlp.linear_fc1",
"visual.blocks.3.mlp.linear_fc2",
"model.visual.blocks.4.attn.proj",
"model.visual.blocks.4.attn.qkv",
"model.visual.blocks.4.mlp.linear_fc1",
"model.visual.blocks.4.mlp.linear_fc2",
"visual.blocks.4.attn.proj",
"visual.blocks.4.attn.qkv_proj",
"visual.blocks.4.mlp.linear_fc1",
"visual.blocks.4.mlp.linear_fc2",
"model.visual.blocks.5.attn.proj",
"model.visual.blocks.5.attn.qkv",
"model.visual.blocks.5.mlp.linear_fc1",
"model.visual.blocks.5.mlp.linear_fc2",
"visual.blocks.5.attn.proj",
"visual.blocks.5.attn.qkv_proj",
"visual.blocks.5.mlp.linear_fc1",
"visual.blocks.5.mlp.linear_fc2",
"model.visual.blocks.6.attn.proj",
"model.visual.blocks.6.attn.qkv",
"model.visual.blocks.6.mlp.linear_fc1",
"model.visual.blocks.6.mlp.linear_fc2",
"visual.blocks.6.attn.proj",
"visual.blocks.6.attn.qkv_proj",
"visual.blocks.6.mlp.linear_fc1",
"visual.blocks.6.mlp.linear_fc2",
"model.visual.blocks.7.attn.proj",
"model.visual.blocks.7.attn.qkv",
"model.visual.blocks.7.mlp.linear_fc1",
"model.visual.blocks.7.mlp.linear_fc2",
"visual.blocks.7.attn.proj",
"visual.blocks.7.attn.qkv_proj",
"visual.blocks.7.mlp.linear_fc1",
"visual.blocks.7.mlp.linear_fc2",
"model.visual.blocks.8.attn.proj",
"model.visual.blocks.8.attn.qkv",
"model.visual.blocks.8.mlp.linear_fc1",
"model.visual.blocks.8.mlp.linear_fc2",
"visual.blocks.8.attn.proj",
"visual.blocks.8.attn.qkv_proj",
"visual.blocks.8.mlp.linear_fc1",
"visual.blocks.8.mlp.linear_fc2",
"model.visual.blocks.9.attn.proj",
"model.visual.blocks.9.attn.qkv",
"model.visual.blocks.9.mlp.linear_fc1",
"model.visual.blocks.9.mlp.linear_fc2",
"visual.blocks.9.attn.proj",
"visual.blocks.9.attn.qkv_proj",
"visual.blocks.9.mlp.linear_fc1",
"visual.blocks.9.mlp.linear_fc2",
"model.visual.blocks.10.attn.proj",
"model.visual.blocks.10.attn.qkv",
"model.visual.blocks.10.mlp.linear_fc1",
"model.visual.blocks.10.mlp.linear_fc2",
"visual.blocks.10.attn.proj",
"visual.blocks.10.attn.qkv_proj",
"visual.blocks.10.mlp.linear_fc1",
"visual.blocks.10.mlp.linear_fc2",
"model.visual.blocks.11.attn.proj",
"model.visual.blocks.11.attn.qkv",
"model.visual.blocks.11.mlp.linear_fc1",
"model.visual.blocks.11.mlp.linear_fc2",
"visual.blocks.11.attn.proj",
"visual.blocks.11.attn.qkv_proj",
"visual.blocks.11.mlp.linear_fc1",
"visual.blocks.11.mlp.linear_fc2",
"model.visual.blocks.12.attn.proj",
"model.visual.blocks.12.attn.qkv",
"model.visual.blocks.12.mlp.linear_fc1",
"model.visual.blocks.12.mlp.linear_fc2",
"visual.blocks.12.attn.proj",
"visual.blocks.12.attn.qkv_proj",
"visual.blocks.12.mlp.linear_fc1",
"visual.blocks.12.mlp.linear_fc2",
"model.visual.blocks.13.attn.proj",
"model.visual.blocks.13.attn.qkv",
"model.visual.blocks.13.mlp.linear_fc1",
"model.visual.blocks.13.mlp.linear_fc2",
"visual.blocks.13.attn.proj",
"visual.blocks.13.attn.qkv_proj",
"visual.blocks.13.mlp.linear_fc1",
"visual.blocks.13.mlp.linear_fc2",
"model.visual.blocks.14.attn.proj",
"model.visual.blocks.14.attn.qkv",
"model.visual.blocks.14.mlp.linear_fc1",
"model.visual.blocks.14.mlp.linear_fc2",
"visual.blocks.14.attn.proj",
"visual.blocks.14.attn.qkv_proj",
"visual.blocks.14.mlp.linear_fc1",
"visual.blocks.14.mlp.linear_fc2",
"model.visual.blocks.15.attn.proj",
"model.visual.blocks.15.attn.qkv",
"model.visual.blocks.15.mlp.linear_fc1",
"model.visual.blocks.15.mlp.linear_fc2",
"visual.blocks.15.attn.proj",
"visual.blocks.15.attn.qkv_proj",
"visual.blocks.15.mlp.linear_fc1",
"visual.blocks.15.mlp.linear_fc2",
"model.visual.blocks.16.attn.proj",
"model.visual.blocks.16.attn.qkv",
"model.visual.blocks.16.mlp.linear_fc1",
"model.visual.blocks.16.mlp.linear_fc2",
"visual.blocks.16.attn.proj",
"visual.blocks.16.attn.qkv_proj",
"visual.blocks.16.mlp.linear_fc1",
"visual.blocks.16.mlp.linear_fc2",
"model.visual.blocks.17.attn.proj",
"model.visual.blocks.17.attn.qkv",
"model.visual.blocks.17.mlp.linear_fc1",
"model.visual.blocks.17.mlp.linear_fc2",
"visual.blocks.17.attn.proj",
"visual.blocks.17.attn.qkv_proj",
"visual.blocks.17.mlp.linear_fc1",
"visual.blocks.17.mlp.linear_fc2",
"model.visual.blocks.18.attn.proj",
"model.visual.blocks.18.attn.qkv",
"model.visual.blocks.18.mlp.linear_fc1",
"model.visual.blocks.18.mlp.linear_fc2",
"visual.blocks.18.attn.proj",
"visual.blocks.18.attn.qkv_proj",
"visual.blocks.18.mlp.linear_fc1",
"visual.blocks.18.mlp.linear_fc2",
"model.visual.blocks.19.attn.proj",
"model.visual.blocks.19.attn.qkv",
"model.visual.blocks.19.mlp.linear_fc1",
"model.visual.blocks.19.mlp.linear_fc2",
"visual.blocks.19.attn.proj",
"visual.blocks.19.attn.qkv_proj",
"visual.blocks.19.mlp.linear_fc1",
"visual.blocks.19.mlp.linear_fc2",
"model.visual.blocks.20.attn.proj",
"model.visual.blocks.20.attn.qkv",
"model.visual.blocks.20.mlp.linear_fc1",
"model.visual.blocks.20.mlp.linear_fc2",
"visual.blocks.20.attn.proj",
"visual.blocks.20.attn.qkv_proj",
"visual.blocks.20.mlp.linear_fc1",
"visual.blocks.20.mlp.linear_fc2",
"model.visual.blocks.21.attn.proj",
"model.visual.blocks.21.attn.qkv",
"model.visual.blocks.21.mlp.linear_fc1",
"model.visual.blocks.21.mlp.linear_fc2",
"visual.blocks.21.attn.proj",
"visual.blocks.21.attn.qkv_proj",
"visual.blocks.21.mlp.linear_fc1",
"visual.blocks.21.mlp.linear_fc2",
"model.visual.blocks.22.attn.proj",
"model.visual.blocks.22.attn.qkv",
"model.visual.blocks.22.mlp.linear_fc1",
"model.visual.blocks.22.mlp.linear_fc2",
"visual.blocks.22.attn.proj",
"visual.blocks.22.attn.qkv_proj",
"visual.blocks.22.mlp.linear_fc1",
"visual.blocks.22.mlp.linear_fc2",
"model.visual.blocks.23.attn.proj",
"model.visual.blocks.23.attn.qkv",
"model.visual.blocks.23.mlp.linear_fc1",
"model.visual.blocks.23.mlp.linear_fc2",
"visual.blocks.23.attn.proj",
"visual.blocks.23.attn.qkv_proj",
"visual.blocks.23.mlp.linear_fc1",
"visual.blocks.23.mlp.linear_fc2",
"model.visual.blocks.24.attn.proj",
"model.visual.blocks.24.attn.qkv",
"model.visual.blocks.24.mlp.linear_fc1",
"model.visual.blocks.24.mlp.linear_fc2",
"visual.blocks.24.attn.proj",
"visual.blocks.24.attn.qkv_proj",
"visual.blocks.24.mlp.linear_fc1",
"visual.blocks.24.mlp.linear_fc2",
"model.visual.blocks.25.attn.proj",
"model.visual.blocks.25.attn.qkv",
"model.visual.blocks.25.mlp.linear_fc1",
"model.visual.blocks.25.mlp.linear_fc2",
"visual.blocks.25.attn.proj",
"visual.blocks.25.attn.qkv_proj",
"visual.blocks.25.mlp.linear_fc1",
"visual.blocks.25.mlp.linear_fc2",
"model.visual.blocks.26.attn.proj",
"model.visual.blocks.26.attn.qkv",
"model.visual.blocks.26.mlp.linear_fc1",
"model.visual.blocks.26.mlp.linear_fc2",
"visual.blocks.26.attn.proj",
"visual.blocks.26.attn.qkv_proj",
"visual.blocks.26.mlp.linear_fc1",
"visual.blocks.26.mlp.linear_fc2",
"model.visual.deepstack_merger_list.0.linear_fc1",
"model.visual.deepstack_merger_list.0.linear_fc2",
"model.visual.deepstack_merger_list.0.norm",
"visual.deepstack_merger_list.0.linear_fc1",
"visual.deepstack_merger_list.0.linear_fc2",
"visual.deepstack_merger_list.0.norm",
"model.visual.deepstack_merger_list.1.linear_fc1",
"model.visual.deepstack_merger_list.1.linear_fc2",
"model.visual.deepstack_merger_list.1.norm",
"visual.deepstack_merger_list.1.linear_fc1",
"visual.deepstack_merger_list.1.linear_fc2",
"visual.deepstack_merger_list.1.norm",
"model.visual.deepstack_merger_list.2.linear_fc1",
"model.visual.deepstack_merger_list.2.linear_fc2",
"model.visual.deepstack_merger_list.2.norm",
"visual.deepstack_merger_list.2.linear_fc1",
"visual.deepstack_merger_list.2.linear_fc2",
"visual.deepstack_merger_list.2.norm",
"model.visual.merger.linear_fc1",
"model.visual.merger.linear_fc2",
"model.visual.merger.norm",
"model.visual.patch_embed.proj",
"model.visual.pos_embed",
"visual.merger.linear_fc1",
"visual.merger.linear_fc2",
"visual.merger.norm",
"visual.patch_embed.proj",
"visual.pos_embed",
"visual",
"model.visual",
"lm_head",
"model.embed_tokens",
"model.language_model.layers.0.input_layernorm",
"model.language_model.layers.0.mlp.shared_expert_gate",
"model.language_model.layers.0.post_attention_layernorm",
"model.language_model.layers.0.mlp.gate",
"model.language_model.layers.0.linear_attn.A_log",
"model.language_model.layers.0.linear_attn.conv1d",
"model.language_model.layers.0.linear_attn.dt_bias",
"model.language_model.layers.0.linear_attn.in_proj_ba",
"model.language_model.layers.0.linear_attn.in_proj_b",
"model.language_model.layers.0.linear_attn.in_proj_a",
"model.language_model.layers.0.linear_attn.norm",
"model.language_model.layers.1.input_layernorm",
"model.language_model.layers.1.mlp.shared_expert_gate",
"model.language_model.layers.1.post_attention_layernorm",
"model.language_model.layers.1.mlp.gate",
"model.language_model.layers.1.linear_attn.A_log",
"model.language_model.layers.1.linear_attn.conv1d",
"model.language_model.layers.1.linear_attn.dt_bias",
"model.language_model.layers.1.linear_attn.in_proj_ba",
"model.language_model.layers.1.linear_attn.in_proj_b",
"model.language_model.layers.1.linear_attn.in_proj_a",
"model.language_model.layers.1.linear_attn.norm",
"model.language_model.layers.2.input_layernorm",
"model.language_model.layers.2.mlp.shared_expert_gate",
"model.language_model.layers.2.post_attention_layernorm",
"model.language_model.layers.2.mlp.gate",
"model.language_model.layers.2.linear_attn.A_log",
"model.language_model.layers.2.linear_attn.conv1d",
"model.language_model.layers.2.linear_attn.dt_bias",
"model.language_model.layers.2.linear_attn.in_proj_ba",
"model.language_model.layers.2.linear_attn.in_proj_b",
"model.language_model.layers.2.linear_attn.in_proj_a",
"model.language_model.layers.2.linear_attn.norm",
"model.language_model.layers.3.input_layernorm",
"model.language_model.layers.3.mlp.shared_expert_gate",
"model.language_model.layers.3.post_attention_layernorm",
"model.language_model.layers.3.mlp.gate",
"model.language_model.layers.3.self_attn.k_norm",
"model.language_model.layers.3.self_attn.q_norm",
"model.language_model.layers.4.input_layernorm",
"model.language_model.layers.4.mlp.shared_expert_gate",
"model.language_model.layers.4.post_attention_layernorm",
"model.language_model.layers.4.mlp.gate",
"model.language_model.layers.4.linear_attn.A_log",
"model.language_model.layers.4.linear_attn.conv1d",
"model.language_model.layers.4.linear_attn.dt_bias",
"model.language_model.layers.4.linear_attn.in_proj_ba",
"model.language_model.layers.4.linear_attn.in_proj_b",
"model.language_model.layers.4.linear_attn.in_proj_a",
"model.language_model.layers.4.linear_attn.norm",
"model.language_model.layers.5.input_layernorm",
"model.language_model.layers.5.mlp.shared_expert_gate",
"model.language_model.layers.5.post_attention_layernorm",
"model.language_model.layers.5.mlp.gate",
"model.language_model.layers.5.linear_attn.A_log",
"model.language_model.layers.5.linear_attn.conv1d",
"model.language_model.layers.5.linear_attn.dt_bias",
"model.language_model.layers.5.linear_attn.in_proj_ba",
"model.language_model.layers.5.linear_attn.in_proj_b",
"model.language_model.layers.5.linear_attn.in_proj_a",
"model.language_model.layers.5.linear_attn.norm",
"model.language_model.layers.6.input_layernorm",
"model.language_model.layers.6.mlp.shared_expert_gate",
"model.language_model.layers.6.post_attention_layernorm",
"model.language_model.layers.6.mlp.gate",
"model.language_model.layers.6.linear_attn.A_log",
"model.language_model.layers.6.linear_attn.conv1d",
"model.language_model.layers.6.linear_attn.dt_bias",
"model.language_model.layers.6.linear_attn.in_proj_ba",
"model.language_model.layers.6.linear_attn.in_proj_b",
"model.language_model.layers.6.linear_attn.in_proj_a",
"model.language_model.layers.6.linear_attn.norm",
"model.language_model.layers.7.input_layernorm",
"model.language_model.layers.7.mlp.shared_expert_gate",
"model.language_model.layers.7.post_attention_layernorm",
"model.language_model.layers.7.mlp.gate",
"model.language_model.layers.7.self_attn.k_norm",
"model.language_model.layers.7.self_attn.q_norm",
"model.language_model.layers.8.input_layernorm",
"model.language_model.layers.8.mlp.shared_expert_gate",
"model.language_model.layers.8.post_attention_layernorm",
"model.language_model.layers.8.mlp.gate",
"model.language_model.layers.8.linear_attn.A_log",
"model.language_model.layers.8.linear_attn.conv1d",
"model.language_model.layers.8.linear_attn.dt_bias",
"model.language_model.layers.8.linear_attn.in_proj_ba",
"model.language_model.layers.8.linear_attn.in_proj_b",
"model.language_model.layers.8.linear_attn.in_proj_a",
"model.language_model.layers.8.linear_attn.norm",
"model.language_model.layers.9.input_layernorm",
"model.language_model.layers.9.mlp.shared_expert_gate",
"model.language_model.layers.9.post_attention_layernorm",
"model.language_model.layers.9.mlp.gate",
"model.language_model.layers.9.linear_attn.A_log",
"model.language_model.layers.9.linear_attn.conv1d",
"model.language_model.layers.9.linear_attn.dt_bias",
"model.language_model.layers.9.linear_attn.in_proj_ba",
"model.language_model.layers.9.linear_attn.in_proj_b",
"model.language_model.layers.9.linear_attn.in_proj_a",
"model.language_model.layers.9.linear_attn.norm",
"model.language_model.layers.10.input_layernorm",
"model.language_model.layers.10.mlp.shared_expert_gate",
"model.language_model.layers.10.post_attention_layernorm",
"model.language_model.layers.10.mlp.gate",
"model.language_model.layers.10.linear_attn.A_log",
"model.language_model.layers.10.linear_attn.conv1d",
"model.language_model.layers.10.linear_attn.dt_bias",
"model.language_model.layers.10.linear_attn.in_proj_ba",
"model.language_model.layers.10.linear_attn.in_proj_b",
"model.language_model.layers.10.linear_attn.in_proj_a",
"model.language_model.layers.10.linear_attn.norm",
"model.language_model.layers.11.input_layernorm",
"model.language_model.layers.11.mlp.shared_expert_gate",
"model.language_model.layers.11.post_attention_layernorm",
"model.language_model.layers.11.mlp.gate",
"model.language_model.layers.11.self_attn.k_norm",
"model.language_model.layers.11.self_attn.q_norm",
"model.language_model.layers.12.input_layernorm",
"model.language_model.layers.12.mlp.shared_expert_gate",
"model.language_model.layers.12.post_attention_layernorm",
"model.language_model.layers.12.mlp.gate",
"model.language_model.layers.12.linear_attn.A_log",
"model.language_model.layers.12.linear_attn.conv1d",
"model.language_model.layers.12.linear_attn.dt_bias",
"model.language_model.layers.12.linear_attn.in_proj_ba",
"model.language_model.layers.12.linear_attn.in_proj_b",
"model.language_model.layers.12.linear_attn.in_proj_a",
"model.language_model.layers.12.linear_attn.norm",
"model.language_model.layers.13.input_layernorm",
"model.language_model.layers.13.mlp.shared_expert_gate",
"model.language_model.layers.13.post_attention_layernorm",
"model.language_model.layers.13.mlp.gate",
"model.language_model.layers.13.linear_attn.A_log",
"model.language_model.layers.13.linear_attn.conv1d",
"model.language_model.layers.13.linear_attn.dt_bias",
"model.language_model.layers.13.linear_attn.in_proj_ba",
"model.language_model.layers.13.linear_attn.in_proj_b",
"model.language_model.layers.13.linear_attn.in_proj_a",
"model.language_model.layers.13.linear_attn.norm",
"model.language_model.layers.14.input_layernorm",
"model.language_model.layers.14.mlp.shared_expert_gate",
"model.language_model.layers.14.post_attention_layernorm",
"model.language_model.layers.14.mlp.gate",
"model.language_model.layers.14.linear_attn.A_log",
"model.language_model.layers.14.linear_attn.conv1d",
"model.language_model.layers.14.linear_attn.dt_bias",
"model.language_model.layers.14.linear_attn.in_proj_ba",
"model.language_model.layers.14.linear_attn.in_proj_b",
"model.language_model.layers.14.linear_attn.in_proj_a",
"model.language_model.layers.14.linear_attn.norm",
"model.language_model.layers.15.input_layernorm",
"model.language_model.layers.15.mlp.shared_expert_gate",
"model.language_model.layers.15.post_attention_layernorm",
"model.language_model.layers.15.mlp.gate",
"model.language_model.layers.15.self_attn.k_norm",
"model.language_model.layers.15.self_attn.q_norm",
"model.language_model.layers.16.input_layernorm",
"model.language_model.layers.16.mlp.shared_expert_gate",
"model.language_model.layers.16.post_attention_layernorm",
"model.language_model.layers.16.mlp.gate",
"model.language_model.layers.16.linear_attn.A_log",
"model.language_model.layers.16.linear_attn.conv1d",
"model.language_model.layers.16.linear_attn.dt_bias",
"model.language_model.layers.16.linear_attn.in_proj_ba",
"model.language_model.layers.16.linear_attn.in_proj_b",
"model.language_model.layers.16.linear_attn.in_proj_a",
"model.language_model.layers.16.linear_attn.norm",
"model.language_model.layers.17.input_layernorm",
"model.language_model.layers.17.mlp.shared_expert_gate",
"model.language_model.layers.17.post_attention_layernorm",
"model.language_model.layers.17.mlp.gate",
"model.language_model.layers.17.linear_attn.A_log",
"model.language_model.layers.17.linear_attn.conv1d",
"model.language_model.layers.17.linear_attn.dt_bias",
"model.language_model.layers.17.linear_attn.in_proj_ba",
"model.language_model.layers.17.linear_attn.in_proj_b",
"model.language_model.layers.17.linear_attn.in_proj_a",
"model.language_model.layers.17.linear_attn.norm",
"model.language_model.layers.18.input_layernorm",
"model.language_model.layers.18.mlp.shared_expert_gate",
"model.language_model.layers.18.post_attention_layernorm",
"model.language_model.layers.18.mlp.gate",
"model.language_model.layers.18.linear_attn.A_log",
"model.language_model.layers.18.linear_attn.conv1d",
"model.language_model.layers.18.linear_attn.dt_bias",
"model.language_model.layers.18.linear_attn.in_proj_ba",
"model.language_model.layers.18.linear_attn.in_proj_b",
"model.language_model.layers.18.linear_attn.in_proj_a",
"model.language_model.layers.18.linear_attn.norm",
"model.language_model.layers.19.input_layernorm",
"model.language_model.layers.19.mlp.shared_expert_gate",
"model.language_model.layers.19.post_attention_layernorm",
"model.language_model.layers.19.mlp.gate",
"model.language_model.layers.19.self_attn.k_norm",
"model.language_model.layers.19.self_attn.q_norm",
"model.language_model.layers.20.input_layernorm",
"model.language_model.layers.20.mlp.shared_expert_gate",
"model.language_model.layers.20.post_attention_layernorm",
"model.language_model.layers.20.mlp.gate",
"model.language_model.layers.20.linear_attn.A_log",
"model.language_model.layers.20.linear_attn.conv1d",
"model.language_model.layers.20.linear_attn.dt_bias",
"model.language_model.layers.20.linear_attn.in_proj_ba",
"model.language_model.layers.20.linear_attn.in_proj_b",
"model.language_model.layers.20.linear_attn.in_proj_a",
"model.language_model.layers.20.linear_attn.norm",
"model.language_model.layers.21.input_layernorm",
"model.language_model.layers.21.mlp.shared_expert_gate",
"model.language_model.layers.21.post_attention_layernorm",
"model.language_model.layers.21.mlp.gate",
"model.language_model.layers.21.linear_attn.A_log",
"model.language_model.layers.21.linear_attn.conv1d",
"model.language_model.layers.21.linear_attn.dt_bias",
"model.language_model.layers.21.linear_attn.in_proj_ba",
"model.language_model.layers.21.linear_attn.in_proj_b",
"model.language_model.layers.21.linear_attn.in_proj_a",
"model.language_model.layers.21.linear_attn.norm",
"model.language_model.layers.22.input_layernorm",
"model.language_model.layers.22.mlp.shared_expert_gate",
"model.language_model.layers.22.post_attention_layernorm",
"model.language_model.layers.22.mlp.gate",
"model.language_model.layers.22.linear_attn.A_log",
"model.language_model.layers.22.linear_attn.conv1d",
"model.language_model.layers.22.linear_attn.dt_bias",
"model.language_model.layers.22.linear_attn.in_proj_ba",
"model.language_model.layers.22.linear_attn.in_proj_b",
"model.language_model.layers.22.linear_attn.in_proj_a",
"model.language_model.layers.22.linear_attn.norm",
"model.language_model.layers.23.input_layernorm",
"model.language_model.layers.23.mlp.shared_expert_gate",
"model.language_model.layers.23.post_attention_layernorm",
"model.language_model.layers.23.mlp.gate",
"model.language_model.layers.23.self_attn.k_norm",
"model.language_model.layers.23.self_attn.q_norm",
"model.language_model.layers.24.input_layernorm",
"model.language_model.layers.24.mlp.shared_expert_gate",
"model.language_model.layers.24.post_attention_layernorm",
"model.language_model.layers.24.mlp.gate",
"model.language_model.layers.24.linear_attn.A_log",
"model.language_model.layers.24.linear_attn.conv1d",
"model.language_model.layers.24.linear_attn.dt_bias",
"model.language_model.layers.24.linear_attn.in_proj_ba",
"model.language_model.layers.24.linear_attn.in_proj_b",
"model.language_model.layers.24.linear_attn.in_proj_a",
"model.language_model.layers.24.linear_attn.norm",
"model.language_model.layers.25.input_layernorm",
"model.language_model.layers.25.mlp.shared_expert_gate",
"model.language_model.layers.25.post_attention_layernorm",
"model.language_model.layers.25.mlp.gate",
"model.language_model.layers.25.linear_attn.A_log",
"model.language_model.layers.25.linear_attn.conv1d",
"model.language_model.layers.25.linear_attn.dt_bias",
"model.language_model.layers.25.linear_attn.in_proj_ba",
"model.language_model.layers.25.linear_attn.in_proj_b",
"model.language_model.layers.25.linear_attn.in_proj_a",
"model.language_model.layers.25.linear_attn.norm",
"model.language_model.layers.26.input_layernorm",
"model.language_model.layers.26.mlp.shared_expert_gate",
"model.language_model.layers.26.post_attention_layernorm",
"model.language_model.layers.26.mlp.gate",
"model.language_model.layers.26.linear_attn.A_log",
"model.language_model.layers.26.linear_attn.conv1d",
"model.language_model.layers.26.linear_attn.dt_bias",
"model.language_model.layers.26.linear_attn.in_proj_ba",
"model.language_model.layers.26.linear_attn.in_proj_b",
"model.language_model.layers.26.linear_attn.in_proj_a",
"model.language_model.layers.26.linear_attn.norm",
"model.language_model.layers.27.input_layernorm",
"model.language_model.layers.27.mlp.shared_expert_gate",
"model.language_model.layers.27.post_attention_layernorm",
"model.language_model.layers.27.mlp.gate",
"model.language_model.layers.27.self_attn.k_norm",
"model.language_model.layers.27.self_attn.q_norm",
"model.language_model.layers.28.input_layernorm",
"model.language_model.layers.28.mlp.shared_expert_gate",
"model.language_model.layers.28.post_attention_layernorm",
"model.language_model.layers.28.mlp.gate",
"model.language_model.layers.28.linear_attn.A_log",
"model.language_model.layers.28.linear_attn.conv1d",
"model.language_model.layers.28.linear_attn.dt_bias",
"model.language_model.layers.28.linear_attn.in_proj_ba",
"model.language_model.layers.28.linear_attn.in_proj_b",
"model.language_model.layers.28.linear_attn.in_proj_a",
"model.language_model.layers.28.linear_attn.norm",
"model.language_model.layers.29.input_layernorm",
"model.language_model.layers.29.mlp.shared_expert_gate",
"model.language_model.layers.29.post_attention_layernorm",
"model.language_model.layers.29.mlp.gate",
"model.language_model.layers.29.linear_attn.A_log",
"model.language_model.layers.29.linear_attn.conv1d",
"model.language_model.layers.29.linear_attn.dt_bias",
"model.language_model.layers.29.linear_attn.in_proj_ba",
"model.language_model.layers.29.linear_attn.in_proj_b",
"model.language_model.layers.29.linear_attn.in_proj_a",
"model.language_model.layers.29.linear_attn.norm",
"model.language_model.layers.30.input_layernorm",
"model.language_model.layers.30.mlp.shared_expert_gate",
"model.language_model.layers.30.post_attention_layernorm",
"model.language_model.layers.30.mlp.gate",
"model.language_model.layers.30.linear_attn.A_log",
"model.language_model.layers.30.linear_attn.conv1d",
"model.language_model.layers.30.linear_attn.dt_bias",
"model.language_model.layers.30.linear_attn.in_proj_ba",
"model.language_model.layers.30.linear_attn.in_proj_b",
"model.language_model.layers.30.linear_attn.in_proj_a",
"model.language_model.layers.30.linear_attn.norm",
"model.language_model.layers.31.input_layernorm",
"model.language_model.layers.31.mlp.shared_expert_gate",
"model.language_model.layers.31.post_attention_layernorm",
"model.language_model.layers.31.mlp.gate",
"model.language_model.layers.31.self_attn.k_norm",
"model.language_model.layers.31.self_attn.q_norm",
"model.language_model.layers.32.input_layernorm",
"model.language_model.layers.32.mlp.shared_expert_gate",
"model.language_model.layers.32.post_attention_layernorm",
"model.language_model.layers.32.mlp.gate",
"model.language_model.layers.32.linear_attn.A_log",
"model.language_model.layers.32.linear_attn.conv1d",
"model.language_model.layers.32.linear_attn.dt_bias",
"model.language_model.layers.32.linear_attn.in_proj_ba",
"model.language_model.layers.32.linear_attn.in_proj_b",
"model.language_model.layers.32.linear_attn.in_proj_a",
"model.language_model.layers.32.linear_attn.norm",
"model.language_model.layers.33.input_layernorm",
"model.language_model.layers.33.mlp.shared_expert_gate",
"model.language_model.layers.33.post_attention_layernorm",
"model.language_model.layers.33.mlp.gate",
"model.language_model.layers.33.linear_attn.A_log",
"model.language_model.layers.33.linear_attn.conv1d",
"model.language_model.layers.33.linear_attn.dt_bias",
"model.language_model.layers.33.linear_attn.in_proj_ba",
"model.language_model.layers.33.linear_attn.in_proj_b",
"model.language_model.layers.33.linear_attn.in_proj_a",
"model.language_model.layers.33.linear_attn.norm",
"model.language_model.layers.34.input_layernorm",
"model.language_model.layers.34.mlp.shared_expert_gate",
"model.language_model.layers.34.post_attention_layernorm",
"model.language_model.layers.34.mlp.gate",
"model.language_model.layers.34.linear_attn.A_log",
"model.language_model.layers.34.linear_attn.conv1d",
"model.language_model.layers.34.linear_attn.dt_bias",
"model.language_model.layers.34.linear_attn.in_proj_ba",
"model.language_model.layers.34.linear_attn.in_proj_b",
"model.language_model.layers.34.linear_attn.in_proj_a",
"model.language_model.layers.34.linear_attn.norm",
"model.language_model.layers.35.input_layernorm",
"model.language_model.layers.35.mlp.shared_expert_gate",
"model.language_model.layers.35.post_attention_layernorm",
"model.language_model.layers.35.mlp.gate",
"model.language_model.layers.35.self_attn.k_norm",
"model.language_model.layers.35.self_attn.q_norm",
"model.language_model.layers.36.input_layernorm",
"model.language_model.layers.36.mlp.shared_expert_gate",
"model.language_model.layers.36.post_attention_layernorm",
"model.language_model.layers.36.mlp.gate",
"model.language_model.layers.36.linear_attn.A_log",
"model.language_model.layers.36.linear_attn.conv1d",
"model.language_model.layers.36.linear_attn.dt_bias",
"model.language_model.layers.36.linear_attn.in_proj_ba",
"model.language_model.layers.36.linear_attn.in_proj_b",
"model.language_model.layers.36.linear_attn.in_proj_a",
"model.language_model.layers.36.linear_attn.norm",
"model.language_model.layers.37.input_layernorm",
"model.language_model.layers.37.mlp.shared_expert_gate",
"model.language_model.layers.37.post_attention_layernorm",
"model.language_model.layers.37.mlp.gate",
"model.language_model.layers.37.linear_attn.A_log",
"model.language_model.layers.37.linear_attn.conv1d",
"model.language_model.layers.37.linear_attn.dt_bias",
"model.language_model.layers.37.linear_attn.in_proj_ba",
"model.language_model.layers.37.linear_attn.in_proj_b",
"model.language_model.layers.37.linear_attn.in_proj_a",
"model.language_model.layers.37.linear_attn.norm",
"model.language_model.layers.38.input_layernorm",
"model.language_model.layers.38.mlp.shared_expert_gate",
"model.language_model.layers.38.post_attention_layernorm",
"model.language_model.layers.38.mlp.gate",
"model.language_model.layers.38.linear_attn.A_log",
"model.language_model.layers.38.linear_attn.conv1d",
"model.language_model.layers.38.linear_attn.dt_bias",
"model.language_model.layers.38.linear_attn.in_proj_ba",
"model.language_model.layers.38.linear_attn.in_proj_b",
"model.language_model.layers.38.linear_attn.in_proj_a",
"model.language_model.layers.38.linear_attn.norm",
"model.language_model.layers.39.input_layernorm",
"model.language_model.layers.39.mlp.shared_expert_gate",
"model.language_model.layers.39.post_attention_layernorm",
"model.language_model.layers.39.mlp.gate",
"model.language_model.layers.39.self_attn.k_norm",
"model.language_model.layers.39.self_attn.q_norm",
"model.language_model.layers.40.input_layernorm",
"model.language_model.layers.40.mlp.shared_expert_gate",
"model.language_model.layers.40.post_attention_layernorm",
"model.language_model.layers.40.mlp.gate",
"model.language_model.layers.40.linear_attn.A_log",
"model.language_model.layers.40.linear_attn.conv1d",
"model.language_model.layers.40.linear_attn.dt_bias",
"model.language_model.layers.40.linear_attn.in_proj_ba",
"model.language_model.layers.40.linear_attn.in_proj_b",
"model.language_model.layers.40.linear_attn.in_proj_a",
"model.language_model.layers.40.linear_attn.norm",
"model.language_model.layers.41.input_layernorm",
"model.language_model.layers.41.mlp.shared_expert_gate",
"model.language_model.layers.41.post_attention_layernorm",
"model.language_model.layers.41.mlp.gate",
"model.language_model.layers.41.linear_attn.A_log",
"model.language_model.layers.41.linear_attn.conv1d",
"model.language_model.layers.41.linear_attn.dt_bias",
"model.language_model.layers.41.linear_attn.in_proj_ba",
"model.language_model.layers.41.linear_attn.in_proj_b",
"model.language_model.layers.41.linear_attn.in_proj_a",
"model.language_model.layers.41.linear_attn.norm",
"model.language_model.layers.42.input_layernorm",
"model.language_model.layers.42.mlp.shared_expert_gate",
"model.language_model.layers.42.post_attention_layernorm",
"model.language_model.layers.42.mlp.gate",
"model.language_model.layers.42.linear_attn.A_log",
"model.language_model.layers.42.linear_attn.conv1d",
"model.language_model.layers.42.linear_attn.dt_bias",
"model.language_model.layers.42.linear_attn.in_proj_ba",
"model.language_model.layers.42.linear_attn.in_proj_b",
"model.language_model.layers.42.linear_attn.in_proj_a",
"model.language_model.layers.42.linear_attn.norm",
"model.language_model.layers.43.input_layernorm",
"model.language_model.layers.43.mlp.shared_expert_gate",
"model.language_model.layers.43.post_attention_layernorm",
"model.language_model.layers.43.mlp.gate",
"model.language_model.layers.43.self_attn.k_norm",
"model.language_model.layers.43.self_attn.q_norm",
"model.language_model.layers.44.input_layernorm",
"model.language_model.layers.44.mlp.shared_expert_gate",
"model.language_model.layers.44.post_attention_layernorm",
"model.language_model.layers.44.mlp.gate",
"model.language_model.layers.44.linear_attn.A_log",
"model.language_model.layers.44.linear_attn.conv1d",
"model.language_model.layers.44.linear_attn.dt_bias",
"model.language_model.layers.44.linear_attn.in_proj_ba",
"model.language_model.layers.44.linear_attn.in_proj_b",
"model.language_model.layers.44.linear_attn.in_proj_a",
"model.language_model.layers.44.linear_attn.norm",
"model.language_model.layers.45.input_layernorm",
"model.language_model.layers.45.mlp.shared_expert_gate",
"model.language_model.layers.45.post_attention_layernorm",
"model.language_model.layers.45.mlp.gate",
"model.language_model.layers.45.linear_attn.A_log",
"model.language_model.layers.45.linear_attn.conv1d",
"model.language_model.layers.45.linear_attn.dt_bias",
"model.language_model.layers.45.linear_attn.in_proj_ba",
"model.language_model.layers.45.linear_attn.in_proj_b",
"model.language_model.layers.45.linear_attn.in_proj_a",
"model.language_model.layers.45.linear_attn.norm",
"model.language_model.layers.46.input_layernorm",
"model.language_model.layers.46.mlp.shared_expert_gate",
"model.language_model.layers.46.post_attention_layernorm",
"model.language_model.layers.46.mlp.gate",
"model.language_model.layers.46.linear_attn.A_log",
"model.language_model.layers.46.linear_attn.conv1d",
"model.language_model.layers.46.linear_attn.dt_bias",
"model.language_model.layers.46.linear_attn.in_proj_ba",
"model.language_model.layers.46.linear_attn.in_proj_b",
"model.language_model.layers.46.linear_attn.in_proj_a",
"model.language_model.layers.46.linear_attn.norm",
"model.language_model.layers.47.input_layernorm",
"model.language_model.layers.47.mlp.shared_expert_gate",
"model.language_model.layers.47.post_attention_layernorm",
"model.language_model.layers.47.mlp.gate",
"model.language_model.layers.47.self_attn.k_norm",
"model.language_model.layers.47.self_attn.q_norm",
"model.language_model.layers.48.input_layernorm",
"model.language_model.layers.48.mlp.shared_expert_gate",
"model.language_model.layers.48.post_attention_layernorm",
"model.language_model.layers.48.mlp.gate",
"model.language_model.layers.48.linear_attn.A_log",
"model.language_model.layers.48.linear_attn.conv1d",
"model.language_model.layers.48.linear_attn.dt_bias",
"model.language_model.layers.48.linear_attn.in_proj_ba",
"model.language_model.layers.48.linear_attn.in_proj_b",
"model.language_model.layers.48.linear_attn.in_proj_a",
"model.language_model.layers.48.linear_attn.norm",
"model.language_model.layers.49.input_layernorm",
"model.language_model.layers.49.mlp.shared_expert_gate",
"model.language_model.layers.49.post_attention_layernorm",
"model.language_model.layers.49.mlp.gate",
"model.language_model.layers.49.linear_attn.A_log",
"model.language_model.layers.49.linear_attn.conv1d",
"model.language_model.layers.49.linear_attn.dt_bias",
"model.language_model.layers.49.linear_attn.in_proj_ba",
"model.language_model.layers.49.linear_attn.in_proj_b",
"model.language_model.layers.49.linear_attn.in_proj_a",
"model.language_model.layers.49.linear_attn.norm",
"model.language_model.layers.50.input_layernorm",
"model.language_model.layers.50.mlp.shared_expert_gate",
"model.language_model.layers.50.post_attention_layernorm",
"model.language_model.layers.50.mlp.gate",
"model.language_model.layers.50.linear_attn.A_log",
"model.language_model.layers.50.linear_attn.conv1d",
"model.language_model.layers.50.linear_attn.dt_bias",
"model.language_model.layers.50.linear_attn.in_proj_ba",
"model.language_model.layers.50.linear_attn.in_proj_b",
"model.language_model.layers.50.linear_attn.in_proj_a",
"model.language_model.layers.50.linear_attn.norm",
"model.language_model.layers.51.input_layernorm",
"model.language_model.layers.51.mlp.shared_expert_gate",
"model.language_model.layers.51.post_attention_layernorm",
"model.language_model.layers.51.mlp.gate",
"model.language_model.layers.51.self_attn.k_norm",
"model.language_model.layers.51.self_attn.q_norm",
"model.language_model.layers.52.input_layernorm",
"model.language_model.layers.52.mlp.shared_expert_gate",
"model.language_model.layers.52.post_attention_layernorm",
"model.language_model.layers.52.mlp.gate",
"model.language_model.layers.52.linear_attn.A_log",
"model.language_model.layers.52.linear_attn.conv1d",
"model.language_model.layers.52.linear_attn.dt_bias",
"model.language_model.layers.52.linear_attn.in_proj_ba",
"model.language_model.layers.52.linear_attn.in_proj_b",
"model.language_model.layers.52.linear_attn.in_proj_a",
"model.language_model.layers.52.linear_attn.norm",
"model.language_model.layers.53.input_layernorm",
"model.language_model.layers.53.mlp.shared_expert_gate",
"model.language_model.layers.53.post_attention_layernorm",
"model.language_model.layers.53.mlp.gate",
"model.language_model.layers.53.linear_attn.A_log",
"model.language_model.layers.53.linear_attn.conv1d",
"model.language_model.layers.53.linear_attn.dt_bias",
"model.language_model.layers.53.linear_attn.in_proj_ba",
"model.language_model.layers.53.linear_attn.in_proj_b",
"model.language_model.layers.53.linear_attn.in_proj_a",
"model.language_model.layers.53.linear_attn.norm",
"model.language_model.layers.54.input_layernorm",
"model.language_model.layers.54.mlp.shared_expert_gate",
"model.language_model.layers.54.post_attention_layernorm",
"model.language_model.layers.54.mlp.gate",
"model.language_model.layers.54.linear_attn.A_log",
"model.language_model.layers.54.linear_attn.conv1d",
"model.language_model.layers.54.linear_attn.dt_bias",
"model.language_model.layers.54.linear_attn.in_proj_ba",
"model.language_model.layers.54.linear_attn.in_proj_b",
"model.language_model.layers.54.linear_attn.in_proj_a",
"model.language_model.layers.54.linear_attn.norm",
"model.language_model.layers.55.input_layernorm",
"model.language_model.layers.55.mlp.shared_expert_gate",
"model.language_model.layers.55.post_attention_layernorm",
"model.language_model.layers.55.mlp.gate",
"model.language_model.layers.55.self_attn.k_norm",
"model.language_model.layers.55.self_attn.q_norm",
"model.language_model.layers.56.input_layernorm",
"model.language_model.layers.56.mlp.shared_expert_gate",
"model.language_model.layers.56.post_attention_layernorm",
"model.language_model.layers.56.mlp.gate",
"model.language_model.layers.56.linear_attn.A_log",
"model.language_model.layers.56.linear_attn.conv1d",
"model.language_model.layers.56.linear_attn.dt_bias",
"model.language_model.layers.56.linear_attn.in_proj_ba",
"model.language_model.layers.56.linear_attn.in_proj_b",
"model.language_model.layers.56.linear_attn.in_proj_a",
"model.language_model.layers.56.linear_attn.norm",
"model.language_model.layers.57.input_layernorm",
"model.language_model.layers.57.mlp.shared_expert_gate",
"model.language_model.layers.57.post_attention_layernorm",
"model.language_model.layers.57.mlp.gate",
"model.language_model.layers.57.linear_attn.A_log",
"model.language_model.layers.57.linear_attn.conv1d",
"model.language_model.layers.57.linear_attn.dt_bias",
"model.language_model.layers.57.linear_attn.in_proj_ba",
"model.language_model.layers.57.linear_attn.in_proj_b",
"model.language_model.layers.57.linear_attn.in_proj_a",
"model.language_model.layers.57.linear_attn.norm",
"model.language_model.layers.58.input_layernorm",
"model.language_model.layers.58.mlp.shared_expert_gate",
"model.language_model.layers.58.post_attention_layernorm",
"model.language_model.layers.58.mlp.gate",
"model.language_model.layers.58.linear_attn.A_log",
"model.language_model.layers.58.linear_attn.conv1d",
"model.language_model.layers.58.linear_attn.dt_bias",
"model.language_model.layers.58.linear_attn.in_proj_ba",
"model.language_model.layers.58.linear_attn.in_proj_b",
"model.language_model.layers.58.linear_attn.in_proj_a",
"model.language_model.layers.58.linear_attn.norm",
"model.language_model.layers.59.input_layernorm",
"model.language_model.layers.59.mlp.shared_expert_gate",
"model.language_model.layers.59.post_attention_layernorm",
"model.language_model.layers.59.mlp.gate",
"model.language_model.layers.59.self_attn.k_norm",
"model.language_model.layers.59.self_attn.q_norm",
"model.language_model.layers.60.input_layernorm",
"model.language_model.layers.60.mlp.shared_expert_gate",
"model.language_model.layers.60.post_attention_layernorm",
"model.language_model.layers.60.mlp.gate",
"model.language_model.layers.60.linear_attn.A_log",
"model.language_model.layers.60.linear_attn.conv1d",
"model.language_model.layers.60.linear_attn.dt_bias",
"model.language_model.layers.60.linear_attn.in_proj_ba",
"model.language_model.layers.60.linear_attn.in_proj_b",
"model.language_model.layers.60.linear_attn.in_proj_a",
"model.language_model.layers.60.linear_attn.norm",
"model.language_model.layers.61.input_layernorm",
"model.language_model.layers.61.mlp.shared_expert_gate",
"model.language_model.layers.61.post_attention_layernorm",
"model.language_model.layers.61.mlp.gate",
"model.language_model.layers.61.linear_attn.A_log",
"model.language_model.layers.61.linear_attn.conv1d",
"model.language_model.layers.61.linear_attn.dt_bias",
"model.language_model.layers.61.linear_attn.in_proj_ba",
"model.language_model.layers.61.linear_attn.in_proj_b",
"model.language_model.layers.61.linear_attn.in_proj_a",
"model.language_model.layers.61.linear_attn.norm",
"model.language_model.layers.62.input_layernorm",
"model.language_model.layers.62.mlp.shared_expert_gate",
"model.language_model.layers.62.post_attention_layernorm",
"model.language_model.layers.62.mlp.gate",
"model.language_model.layers.62.linear_attn.A_log",
"model.language_model.layers.62.linear_attn.conv1d",
"model.language_model.layers.62.linear_attn.dt_bias",
"model.language_model.layers.62.linear_attn.in_proj_ba",
"model.language_model.layers.62.linear_attn.in_proj_b",
"model.language_model.layers.62.linear_attn.in_proj_a",
"model.language_model.layers.62.linear_attn.norm",
"model.language_model.layers.63.input_layernorm",
"model.language_model.layers.63.mlp.shared_expert_gate",
"model.language_model.layers.63.post_attention_layernorm",
"model.language_model.layers.63.mlp.gate",
"model.language_model.layers.63.self_attn.k_norm",
"model.language_model.layers.63.self_attn.q_norm",
"mtp.layers.0.input_layernorm",
"mtp.layers.0.mlp.gate",
"mtp.layers.0.mlp.shared_expert_gate",
"mtp.layers.0.post_attention_layernorm",
"mtp.layers.0.self_attn.k_norm",
"mtp.layers.0.self_attn.q_norm",
"mtp.fc",
"mtp.norm",
"mtp.pre_fc_norm_embedding",
"mtp.pre_fc_norm_hidden"
],
"weight_block_size": [
128,
128
]
}
} |