File size: 10,806 Bytes
ed6dd53 |
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 |
llama_model_loader: loaded meta data with 25 key-value pairs and 273 tensors from NuminaMath-7B-TIR-IMat-GGUF/NuminaMath-7B-TIR.Q8_0.gguf.hardlink.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.name str = NuminaMath-7B-TIR
llama_model_loader: - kv 2: llama.block_count u32 = 30
llama_model_loader: - kv 3: llama.context_length u32 = 4096
llama_model_loader: - kv 4: llama.embedding_length u32 = 4096
llama_model_loader: - kv 5: llama.feed_forward_length u32 = 11008
llama_model_loader: - kv 6: llama.attention.head_count u32 = 32
llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 32
llama_model_loader: - kv 8: llama.rope.freq_base f32 = 10000.000000
llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 10: general.file_type u32 = 7
llama_model_loader: - kv 11: llama.vocab_size u32 = 102400
llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 13: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 14: tokenizer.ggml.pre str = deepseek-llm
llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,102400] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 16: tokenizer.ggml.token_type arr[i32,102400] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 17: tokenizer.ggml.merges arr[str,99757] = ["Ġ Ġ", "Ġ t", "Ġ a", "i n", "h e...
llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 100000
llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 100001
llama_model_loader: - kv 20: tokenizer.ggml.padding_token_id u32 = 100001
llama_model_loader: - kv 21: tokenizer.ggml.add_bos_token bool = true
llama_model_loader: - kv 22: tokenizer.ggml.add_eos_token bool = false
llama_model_loader: - kv 23: tokenizer.chat_template str = {% for message in messages %}{% if (m...
llama_model_loader: - kv 24: general.quantization_version u32 = 2
llama_model_loader: - type f32: 61 tensors
llama_model_loader: - type q8_0: 212 tensors
llm_load_vocab: special tokens cache size = 2400
llm_load_vocab: token to piece cache size = 0.6659 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 102400
llm_load_print_meta: n_merges = 99757
llm_load_print_meta: vocab_only = 0
llm_load_print_meta: n_ctx_train = 4096
llm_load_print_meta: n_embd = 4096
llm_load_print_meta: n_layer = 30
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 32
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_swa = 0
llm_load_print_meta: n_embd_head_k = 128
llm_load_print_meta: n_embd_head_v = 128
llm_load_print_meta: n_gqa = 1
llm_load_print_meta: n_embd_k_gqa = 4096
llm_load_print_meta: n_embd_v_gqa = 4096
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-06
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale = 0.0e+00
llm_load_print_meta: n_ff = 11008
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: causal attn = 1
llm_load_print_meta: pooling type = 0
llm_load_print_meta: rope type = 0
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn = 4096
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: ssm_d_conv = 0
llm_load_print_meta: ssm_d_inner = 0
llm_load_print_meta: ssm_d_state = 0
llm_load_print_meta: ssm_dt_rank = 0
llm_load_print_meta: model type = ?B
llm_load_print_meta: model ftype = Q8_0
llm_load_print_meta: model params = 6.91 B
llm_load_print_meta: model size = 6.84 GiB (8.50 BPW)
llm_load_print_meta: general.name = NuminaMath-7B-TIR
llm_load_print_meta: BOS token = 100000 '<｜begin▁of▁sentence｜>'
llm_load_print_meta: EOS token = 100001 '<｜end▁of▁sentence｜>'
llm_load_print_meta: PAD token = 100001 '<｜end▁of▁sentence｜>'
llm_load_print_meta: LF token = 126 'Ä'
llm_load_print_meta: max token length = 256
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes
llm_load_tensors: ggml ctx size = 0.26 MiB
llm_load_tensors: offloading 30 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 31/31 layers to GPU
llm_load_tensors: CPU buffer size = 425.00 MiB
llm_load_tensors: CUDA0 buffer size = 6577.84 MiB
..........................................................................................
llama_new_context_with_model: n_ctx = 512
llama_new_context_with_model: n_batch = 512
llama_new_context_with_model: n_ubatch = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base = 10000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: CUDA0 KV buffer size = 240.00 MiB
llama_new_context_with_model: KV self size = 240.00 MiB, K (f16): 120.00 MiB, V (f16): 120.00 MiB
llama_new_context_with_model: CUDA_Host output buffer size = 0.39 MiB
llama_new_context_with_model: CUDA0 compute buffer size = 208.00 MiB
llama_new_context_with_model: CUDA_Host compute buffer size = 9.01 MiB
llama_new_context_with_model: graph nodes = 966
llama_new_context_with_model: graph splits = 2
system_info: n_threads = 25 / 32 | AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | AVX512_BF16 = 1 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 |
compute_imatrix: tokenizing the input ..
compute_imatrix: tokenization took 219.795 ms
compute_imatrix: computing over 139 chunks with batch_size 512
compute_imatrix: 0.66 seconds per pass - ETA 1.53 minutes
[1]10.4314,[2]7.3682,[3]6.7831,[4]8.2509,[5]7.7539,[6]7.2769,[7]8.2499,[8]8.2793,[9]9.5899,
save_imatrix: stored collected data after 10 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[10]9.8051,[11]9.0158,[12]9.8822,[13]10.7192,[14]11.4750,[15]11.7074,[16]12.4342,[17]12.8366,[18]13.0696,[19]13.6454,
save_imatrix: stored collected data after 20 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[20]12.7369,[21]12.7164,[22]13.0572,[23]13.4045,[24]13.0591,[25]13.4993,[26]13.0929,[27]13.5825,[28]13.4809,[29]13.9218,
save_imatrix: stored collected data after 30 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[30]14.3508,[31]14.8240,[32]14.6801,[33]14.0268,[34]13.0593,[35]12.3150,[36]12.1439,[37]12.1304,[38]12.0899,[39]11.8205,
save_imatrix: stored collected data after 40 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[40]11.7968,[41]11.4809,[42]11.2521,[43]11.4326,[44]11.5349,[45]11.8091,[46]11.8210,[47]12.4688,[48]12.9043,[49]13.2747,
save_imatrix: stored collected data after 50 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[50]13.5610,[51]13.7512,[52]13.5889,[53]13.7792,[54]14.0260,[55]14.1128,[56]13.9351,[57]13.8070,[58]13.7664,[59]13.9588,
save_imatrix: stored collected data after 60 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[60]14.1955,[61]14.4787,[62]14.5778,[63]14.6177,[64]14.6769,[65]14.6685,[66]14.6656,[67]14.6345,[68]14.5578,[69]14.6843,
save_imatrix: stored collected data after 70 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[70]14.8954,[71]14.8467,[72]14.8260,[73]14.7263,[74]14.6219,[75]14.4769,[76]14.3974,[77]14.3304,[78]14.2765,[79]14.1135,
save_imatrix: stored collected data after 80 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[80]14.0793,[81]14.0205,[82]13.9517,[83]13.8239,[84]13.7387,[85]13.6672,[86]13.5425,[87]13.4674,[88]13.4413,[89]13.4553,
save_imatrix: stored collected data after 90 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[90]13.3877,[91]13.4239,[92]13.4322,[93]13.3130,[94]13.2679,[95]13.2266,[96]13.3477,[97]13.4149,[98]13.4163,[99]13.2541,
save_imatrix: stored collected data after 100 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[100]13.0952,[101]12.9394,[102]12.7769,[103]12.6021,[104]12.4604,[105]12.3279,[106]12.1804,[107]12.0326,[108]11.9975,[109]12.0266,
save_imatrix: stored collected data after 110 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[110]12.0979,[111]12.2131,[112]12.3274,[113]12.4241,[114]12.6192,[115]12.7171,[116]12.7818,[117]12.7623,[118]12.8884,[119]12.8693,
save_imatrix: stored collected data after 120 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[120]12.8420,[121]12.7717,[122]12.7185,[123]12.8016,[124]12.8760,[125]12.8461,[126]12.8485,[127]12.8573,[128]12.9072,[129]12.9172,
save_imatrix: stored collected data after 130 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
[130]12.9305,[131]12.9718,[132]12.9349,[133]12.8673,[134]12.9903,[135]13.1251,[136]13.2243,[137]13.3934,[138]13.5698,[139]13.6705,
save_imatrix: stored collected data after 139 chunks in NuminaMath-7B-TIR-IMat-GGUF/imatrix.dat
llama_print_timings: load time = 9195.41 ms
llama_print_timings: sample time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second)
llama_print_timings: prompt eval time = 71105.13 ms / 71168 tokens ( 1.00 ms per token, 1000.88 tokens per second)
llama_print_timings: eval time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second)
llama_print_timings: total time = 80417.25 ms / 71169 tokens
Final estimate: PPL = 13.6705 +/- 0.25616
|