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main: build = 3003 (d298382a)
main: built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
main: seed  = 1716752123
llama_model_loader: loaded meta data with 27 key-value pairs and 197 tensors from Phi-3-mini-128k-instruct-IMat-GGUF/Phi-3-mini-128k-instruct.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              = phi3
llama_model_loader: - kv   1:                               general.name str              = Phi3
llama_model_loader: - kv   2:                        phi3.context_length u32              = 131072
llama_model_loader: - kv   3:  phi3.rope.scaling.original_context_length u32              = 4096
llama_model_loader: - kv   4:                      phi3.embedding_length u32              = 3072
llama_model_loader: - kv   5:                   phi3.feed_forward_length u32              = 8192
llama_model_loader: - kv   6:                           phi3.block_count u32              = 32
llama_model_loader: - kv   7:                  phi3.attention.head_count u32              = 32
llama_model_loader: - kv   8:               phi3.attention.head_count_kv u32              = 32
llama_model_loader: - kv   9:      phi3.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                  phi3.rope.dimension_count u32              = 96
llama_model_loader: - kv  11:                        phi3.rope.freq_base f32              = 10000.000000
llama_model_loader: - kv  12:                          general.file_type u32              = 0
llama_model_loader: - kv  13:              phi3.rope.scaling.attn_factor f32              = 1.190238
llama_model_loader: - kv  14:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  15:                         tokenizer.ggml.pre str              = default
llama_model_loader: - kv  16:                      tokenizer.ggml.tokens arr[str,32064]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv  17:                      tokenizer.ggml.scores arr[f32,32064]   = [-1000.000000, -1000.000000, -1000.00...
llama_model_loader: - kv  18:                  tokenizer.ggml.token_type arr[i32,32064]   = [3, 3, 4, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv  19:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  20:                tokenizer.ggml.eos_token_id u32              = 32000
llama_model_loader: - kv  21:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  22:            tokenizer.ggml.padding_token_id u32              = 32000
llama_model_loader: - kv  23:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  24:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  25:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
llama_model_loader: - kv  26:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  197 tensors
llm_load_vocab: special tokens definition check successful ( 323/32064 ).
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = phi3
llm_load_print_meta: vocab type       = SPM
llm_load_print_meta: n_vocab          = 32064
llm_load_print_meta: n_merges         = 0
llm_load_print_meta: n_ctx_train      = 131072
llm_load_print_meta: n_embd           = 3072
llm_load_print_meta: n_head           = 32
llm_load_print_meta: n_head_kv        = 32
llm_load_print_meta: n_layer          = 32
llm_load_print_meta: n_rot            = 96
llm_load_print_meta: n_embd_head_k    = 96
llm_load_print_meta: n_embd_head_v    = 96
llm_load_print_meta: n_gqa            = 1
llm_load_print_meta: n_embd_k_gqa     = 3072
llm_load_print_meta: n_embd_v_gqa     = 3072
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
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             = 8192
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        = 2
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_yarn_orig_ctx  = 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       = 3B
llm_load_print_meta: model ftype      = all F32
llm_load_print_meta: model params     = 3.82 B
llm_load_print_meta: model size       = 14.23 GiB (32.00 BPW) 
llm_load_print_meta: general.name     = Phi3
llm_load_print_meta: BOS token        = 1 '<s>'
llm_load_print_meta: EOS token        = 32000 '<|endoftext|>'
llm_load_print_meta: UNK token        = 0 '<unk>'
llm_load_print_meta: PAD token        = 32000 '<|endoftext|>'
llm_load_print_meta: LF token         = 13 '<0x0A>'
llm_load_print_meta: EOT token        = 32007 '<|end|>'
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:   no
ggml_cuda_init: CUDA_USE_TENSOR_CORES: yes
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 =    0.22 MiB
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU
llm_load_tensors:        CPU buffer size =   375.75 MiB
llm_load_tensors:      CUDA0 buffer size = 14200.53 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 =   192.00 MiB
llama_new_context_with_model: KV self size  =  192.00 MiB, K (f16):   96.00 MiB, V (f16):   96.00 MiB
llama_new_context_with_model:  CUDA_Host  output buffer size =     0.12 MiB
llama_new_context_with_model:      CUDA0 compute buffer size =    83.00 MiB
llama_new_context_with_model:  CUDA_Host compute buffer size =     7.01 MiB
llama_new_context_with_model: graph nodes  = 1286
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 133.64 ms
compute_imatrix: computing over 234 chunks with batch_size 512
compute_imatrix: 0.32 seconds per pass - ETA 1.23 minutes
[1]6.0727,[2]4.4610,[3]4.4629,[4]4.9370,[5]5.3244,[6]5.4170,[7]4.8496,[8]5.2827,[9]5.5966,
save_imatrix: stored collected data after 10 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[10]5.9047,[11]5.8828,[12]5.4226,[13]5.5632,[14]5.4485,[15]5.8942,[16]5.9986,[17]6.2966,[18]6.4616,[19]6.6562,
save_imatrix: stored collected data after 20 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[20]6.8072,[21]6.8799,[22]7.1044,[23]6.8300,[24]6.6506,[25]6.6546,[26]6.2990,[27]6.0381,[28]5.7430,[29]5.7002,
save_imatrix: stored collected data after 30 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[30]5.8055,[31]5.8773,[32]5.9258,[33]5.9168,[34]5.9704,[35]5.9718,[36]5.7531,[37]5.6171,[38]5.5492,[39]5.5208,
save_imatrix: stored collected data after 40 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[40]5.4923,[41]5.4249,[42]5.4651,[43]5.5062,[44]5.5516,[45]5.6231,[46]5.7071,[47]5.7971,[48]5.9323,[49]6.0424,
save_imatrix: stored collected data after 50 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[50]6.1599,[51]6.2644,[52]6.3634,[53]6.3316,[54]6.2462,[55]6.1791,[56]6.2703,[57]6.3211,[58]6.3341,[59]6.3940,
save_imatrix: stored collected data after 60 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[60]6.4760,[61]6.5040,[62]6.5788,[63]6.6285,[64]6.7074,[65]6.7470,[66]6.7897,[67]6.8378,[68]6.8799,[69]6.9477,
save_imatrix: stored collected data after 70 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[70]6.9901,[71]7.0393,[72]7.0741,[73]7.0324,[74]6.9788,[75]6.9180,[76]6.8588,[77]6.8484,[78]6.7958,[79]6.7419,
save_imatrix: stored collected data after 80 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[80]6.6785,[81]6.6562,[82]6.6094,[83]6.5719,[84]6.5868,[85]6.6086,[86]6.6214,[87]6.6579,[88]6.6725,[89]6.6531,
save_imatrix: stored collected data after 90 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[90]6.6234,[91]6.6468,[92]6.6571,[93]6.6760,[94]6.6899,[95]6.7034,[96]6.7345,[97]6.7548,[98]6.7283,[99]6.6884,
save_imatrix: stored collected data after 100 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[100]6.7032,[101]6.7244,[102]6.7139,[103]6.6792,[104]6.6236,[105]6.6084,[106]6.6134,[107]6.6201,[108]6.5983,[109]6.5869,
save_imatrix: stored collected data after 110 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[110]6.5668,[111]6.5736,[112]6.5833,[113]6.5814,[114]6.5906,[115]6.5858,[116]6.5842,[117]6.5771,[118]6.5829,[119]6.5621,
save_imatrix: stored collected data after 120 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[120]6.5647,[121]6.5506,[122]6.5262,[123]6.5435,[124]6.5348,[125]6.5383,[126]6.5255,[127]6.5257,[128]6.5349,[129]6.5169,
save_imatrix: stored collected data after 130 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[130]6.4927,[131]6.4831,[132]6.4802,[133]6.4305,[134]6.4382,[135]6.4156,[136]6.3964,[137]6.3724,[138]6.3466,[139]6.3174,
save_imatrix: stored collected data after 140 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[140]6.2951,[141]6.2763,[142]6.2547,[143]6.2554,[144]6.2527,[145]6.2348,[146]6.2123,[147]6.2092,[148]6.1993,[149]6.1886,
save_imatrix: stored collected data after 150 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[150]6.1821,[151]6.1677,[152]6.1637,[153]6.1538,[154]6.1412,[155]6.1651,[156]6.1401,[157]6.1342,[158]6.1511,[159]6.1461,
save_imatrix: stored collected data after 160 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[160]6.1502,[161]6.1632,[162]6.1662,[163]6.1865,[164]6.1987,[165]6.2188,[166]6.2278,[167]6.2257,[168]6.2270,[169]6.2340,
save_imatrix: stored collected data after 170 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[170]6.2467,[171]6.2367,[172]6.2370,[173]6.2540,[174]6.2566,[175]6.2740,[176]6.2834,[177]6.2939,[178]6.3006,[179]6.3317,
save_imatrix: stored collected data after 180 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[180]6.3424,[181]6.3923,[182]6.4110,[183]6.4381,[184]6.4432,[185]6.4486,[186]6.4541,[187]6.4579,[188]6.4483,[189]6.4521,
save_imatrix: stored collected data after 190 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[190]6.4586,[191]6.4720,[192]6.4769,[193]6.5062,[194]6.4950,[195]6.4664,[196]6.5076,[197]6.5460,[198]6.5764,[199]6.6271,
save_imatrix: stored collected data after 200 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[200]6.6740,[201]6.6813,[202]6.6861,[203]6.6440,[204]6.6408,[205]6.6470,[206]6.6681,[207]6.6649,[208]6.6679,[209]6.6688,
save_imatrix: stored collected data after 210 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[210]6.6772,[211]6.6909,[212]6.6907,[213]6.6877,[214]6.6944,[215]6.7130,[216]6.7305,[217]6.7338,[218]6.7346,[219]6.7292,
save_imatrix: stored collected data after 220 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[220]6.7205,[221]6.7193,[222]6.7178,[223]6.7324,[224]6.7153,[225]6.7209,[226]6.7047,[227]6.7403,[228]6.7806,[229]6.8252,
save_imatrix: stored collected data after 230 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat
[230]6.8657,[231]6.8871,[232]6.8663,[233]6.8447,[234]6.8193,
save_imatrix: stored collected data after 234 chunks in Phi-3-mini-128k-instruct-IMat-GGUF/imatrix.dat

llama_print_timings:        load time =    2127.07 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 =   52676.50 ms / 119808 tokens (    0.44 ms per token,  2274.41 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 =   55109.70 ms / 119809 tokens

Final estimate: PPL = 6.8193 +/- 0.07007