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imatrix.log

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+build: 3785 (64c6af31) with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
+llama_model_loader: loaded meta data with 38 key-value pairs and 507 tensors from Mistral-Small-Instruct-2409-IMat-GGUF/Mistral-Small-Instruct-2409.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.type str              = model
+llama_model_loader: - kv   2:                               general.name str              = Mistral Small Instruct 2409
+llama_model_loader: - kv   3:                            general.version str              = 2409
+llama_model_loader: - kv   4:                           general.finetune str              = Instruct
+llama_model_loader: - kv   5:                           general.basename str              = Mistral
+llama_model_loader: - kv   6:                         general.size_label str              = Small
+llama_model_loader: - kv   7:                            general.license str              = other
+llama_model_loader: - kv   8:                       general.license.name str              = mrl
+llama_model_loader: - kv   9:                       general.license.link str              = https://mistral.ai/licenses/MRL-0.1.md
+llama_model_loader: - kv  10:                          general.languages arr[str,10]      = ["en", "fr", "de", "es", "it", "pt", ...
+llama_model_loader: - kv  11:                          llama.block_count u32              = 56
+llama_model_loader: - kv  12:                       llama.context_length u32              = 131072
+llama_model_loader: - kv  13:                     llama.embedding_length u32              = 6144
+llama_model_loader: - kv  14:                  llama.feed_forward_length u32              = 16384
+llama_model_loader: - kv  15:                 llama.attention.head_count u32              = 48
+llama_model_loader: - kv  16:              llama.attention.head_count_kv u32              = 8
+llama_model_loader: - kv  17:                       llama.rope.freq_base f32              = 1000000.000000
+llama_model_loader: - kv  18:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
+llama_model_loader: - kv  19:                 llama.attention.key_length u32              = 128
+llama_model_loader: - kv  20:               llama.attention.value_length u32              = 128
+llama_model_loader: - kv  21:                          general.file_type u32              = 7
+llama_model_loader: - kv  22:                           llama.vocab_size u32              = 32768
+llama_model_loader: - kv  23:                 llama.rope.dimension_count u32              = 128
+llama_model_loader: - kv  24:            tokenizer.ggml.add_space_prefix bool             = false
+llama_model_loader: - kv  25:                       tokenizer.ggml.model str              = llama
+llama_model_loader: - kv  26:                         tokenizer.ggml.pre str              = default
+llama_model_loader: - kv  27:                      tokenizer.ggml.tokens arr[str,32768]   = ["<unk>", "<s>", "</s>", "[INST]", "[...
+llama_model_loader: - kv  28:                      tokenizer.ggml.scores arr[f32,32768]   = [-1000.000000, -1000.000000, -1000.00...
+llama_model_loader: - kv  29:                  tokenizer.ggml.token_type arr[i32,32768]   = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
+llama_model_loader: - kv  30:                tokenizer.ggml.bos_token_id u32              = 1
+llama_model_loader: - kv  31:                tokenizer.ggml.eos_token_id u32              = 2
+llama_model_loader: - kv  32:            tokenizer.ggml.unknown_token_id u32              = 0
+llama_model_loader: - kv  33:            tokenizer.ggml.padding_token_id u32              = 2
+llama_model_loader: - kv  34:               tokenizer.ggml.add_bos_token bool             = true
+llama_model_loader: - kv  35:               tokenizer.ggml.add_eos_token bool             = false
+llama_model_loader: - kv  36:                    tokenizer.chat_template str              = {%- if messages[0]["role"] == "system...
+llama_model_loader: - kv  37:               general.quantization_version u32              = 2
+llama_model_loader: - type  f32:  113 tensors
+llama_model_loader: - type q8_0:  394 tensors
+llm_load_vocab: special tokens cache size = 771
+llm_load_vocab: token to piece cache size = 0.1732 MB
+llm_load_print_meta: format           = GGUF V3 (latest)
+llm_load_print_meta: arch             = llama
+llm_load_print_meta: vocab type       = SPM
+llm_load_print_meta: n_vocab          = 32768
+llm_load_print_meta: n_merges         = 0
+llm_load_print_meta: vocab_only       = 0
+llm_load_print_meta: n_ctx_train      = 131072
+llm_load_print_meta: n_embd           = 6144
+llm_load_print_meta: n_layer          = 56
+llm_load_print_meta: n_head           = 48
+llm_load_print_meta: n_head_kv        = 8
+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            = 6
+llm_load_print_meta: n_embd_k_gqa     = 1024
+llm_load_print_meta: n_embd_v_gqa     = 1024
+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             = 16384
+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  = 1000000.0
+llm_load_print_meta: freq_scale_train = 1
+llm_load_print_meta: n_ctx_orig_yarn  = 131072
+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: ssm_dt_b_c_rms   = 0
+llm_load_print_meta: model type       = ?B
+llm_load_print_meta: model ftype      = Q8_0
+llm_load_print_meta: model params     = 22.25 B
+llm_load_print_meta: model size       = 22.02 GiB (8.50 BPW) 
+llm_load_print_meta: general.name     = Mistral Small Instruct 2409
+llm_load_print_meta: BOS token        = 1 '<s>'
+llm_load_print_meta: EOS token        = 2 '</s>'
+llm_load_print_meta: UNK token        = 0 '<unk>'
+llm_load_print_meta: PAD token        = 2 '</s>'
+llm_load_print_meta: LF token         = 781 '<0x0A>'
+llm_load_print_meta: max token length = 48
+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 =    0.47 MiB
+llm_load_tensors: offloading 33 repeating layers to GPU
+llm_load_tensors: offloaded 33/57 layers to GPU
+llm_load_tensors:        CPU buffer size = 22544.65 MiB
+llm_load_tensors:      CUDA0 buffer size = 13044.80 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  = 1000000.0
+llama_new_context_with_model: freq_scale = 1
+llama_kv_cache_init:  CUDA_Host KV buffer size =    46.00 MiB
+llama_kv_cache_init:      CUDA0 KV buffer size =    66.00 MiB
+llama_new_context_with_model: KV self size  =  112.00 MiB, K (f16):   56.00 MiB, V (f16):   56.00 MiB
+llama_new_context_with_model:  CUDA_Host  output buffer size =     0.12 MiB
+llama_new_context_with_model:      CUDA0 compute buffer size =   280.00 MiB
+llama_new_context_with_model:  CUDA_Host compute buffer size =    13.01 MiB
+llama_new_context_with_model: graph nodes  = 1798
+llama_new_context_with_model: graph splits = 257
+
+system_info: n_threads = 25 (n_threads_batch = 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 | RISCV_VECT = 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 94.793 ms
+compute_imatrix: computing over 148 chunks with batch_size 512
+compute_imatrix: 2.04 seconds per pass - ETA 5.02 minutes
+[1]3.2578,[2]2.5472,[3]2.6136,[4]2.6874,[5]3.0332,[6]3.0026,[7]2.7358,[8]3.1186,[9]3.2092,[10]3.5380,[11]3.6618,[12]3.4629,[13]3.6335,[14]3.8547,[15]4.1476,[16]4.2618,[17]4.4422,[18]4.5426,[19]4.6160,[20]4.7419,[21]4.6982,[22]4.5494,[23]4.6684,[24]4.6233,[25]4.6366,[26]4.5111,[27]4.6653,[28]4.6147,[29]4.6997,[30]4.5839,[31]4.4966,[32]4.4114,[33]4.4281,[34]4.4607,[35]4.4212,[36]4.2823,[37]4.1864,[38]4.1108,[39]4.0595,[40]4.0172,[41]4.0269,[42]4.0019,[43]3.9943,[44]3.9540,[45]3.9290,[46]3.9498,[47]3.9423,[48]4.0207,[49]4.0451,[50]4.0061,[51]3.9246,[52]3.9374,[53]3.9481,[54]3.9571,[55]3.9401,[56]3.9288,[57]3.9968,[58]4.0671,[59]4.0987,[60]4.0662,[61]4.0831,[62]4.1117,[63]4.1505,[64]4.2216,[65]4.2418,[66]4.2755,[67]4.3050,[68]4.3357,[69]4.3516,[70]4.3645,[71]4.3298,[72]4.3032,[73]4.2990,[74]4.3122,[75]4.3464,[76]4.3419,[77]4.3671,[78]4.3831,[79]4.3728,[80]4.3743,[81]4.3641,[82]4.3770,[83]4.3886,[84]4.3924,[85]4.4106,[86]4.4055,[87]4.4011,[88]4.3942,[89]4.4035,[90]4.3951,[91]4.3805,[92]4.3712,[93]4.3645,[94]4.3920,[95]4.4133,[96]4.4055,[97]4.4084,[98]4.4046,[99]4.4303,[100]4.3983,[101]4.3979,[102]4.3878,[103]4.4028,[104]4.4163,[105]4.4130,[106]4.3927,[107]4.3670,[108]4.3450,[109]4.3203,[110]4.2957,[111]4.2729,[112]4.2506,[113]4.2273,[114]4.2036,[115]4.1819,[116]4.1885,[117]4.2074,[118]4.2497,[119]4.2920,[120]4.3299,[121]4.3881,[122]4.4360,[123]4.4427,[124]4.4511,[125]4.4282,[126]4.4220,[127]4.4146,[128]4.4161,[129]4.3885,[130]4.3600,[131]4.3846,[132]4.4114,[133]4.4152,[134]4.4138,[135]4.4274,[136]4.4498,[137]4.4582,[138]4.4699,[139]4.4877,[140]4.5007,[141]4.4997,[142]4.5229,[143]4.5358,[144]4.5407,[145]4.5531,[146]4.5524,[147]4.5759,[148]4.5945,
+Final estimate: PPL = 4.5945 +/- 0.05201
+
+llama_perf_context_print:        load time =    4372.23 ms
+llama_perf_context_print: prompt eval time =  283454.45 ms / 75776 tokens (    3.74 ms per token,   267.33 tokens per second)
+llama_perf_context_print:        eval time =       0.00 ms /     1 runs   (    0.00 ms per token,      inf tokens per second)
+llama_perf_context_print:       total time =  286343.85 ms / 75777 tokens