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imatrix.log

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+llama_model_loader: loaded meta data with 26 key-value pairs and 195 tensors from Phi-3-mini-4k-instruct-IMat-GGUF/Phi-3-mini-4k-instruct.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              = phi3
+llama_model_loader: - kv   1:                               general.name str              = Phi3
+llama_model_loader: - kv   2:                        phi3.context_length u32              = 4096
+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              = 7
+llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = llama
+llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = default
+llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,32064]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
+llama_model_loader: - kv  16:                      tokenizer.ggml.scores arr[f32,32064]   = [-1000.000000, -1000.000000, -1000.00...
+llama_model_loader: - kv  17:                  tokenizer.ggml.token_type arr[i32,32064]   = [3, 3, 4, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
+llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 1
+llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 32000
+llama_model_loader: - kv  20:            tokenizer.ggml.unknown_token_id u32              = 0
+llama_model_loader: - kv  21:            tokenizer.ggml.padding_token_id u32              = 32000
+llama_model_loader: - kv  22:               tokenizer.ggml.add_bos_token bool             = false
+llama_model_loader: - kv  23:               tokenizer.ggml.add_eos_token bool             = false
+llama_model_loader: - kv  24:                    tokenizer.chat_template str              = {% for message in messages %}{% if me...
+llama_model_loader: - kv  25:               general.quantization_version u32              = 2
+llama_model_loader: - type  f32:   65 tensors
+llama_model_loader: - type q8_0:  130 tensors
+llm_load_vocab: special tokens cache size = 323
+llm_load_vocab: token to piece cache size = 0.1687 MB
+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      = 4096
+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_swa            = 0
+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_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       = 3B
+llm_load_print_meta: model ftype      = Q8_0
+llm_load_print_meta: model params     = 3.82 B
+llm_load_print_meta: model size       = 3.78 GiB (8.50 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|>'
+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 =    0.20 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 =    99.81 MiB
+llm_load_tensors:      CUDA0 buffer size =  3772.57 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 97.069 ms
+compute_imatrix: computing over 151 chunks with batch_size 512
+compute_imatrix: 0.36 seconds per pass - ETA 0.88 minutes
+[1]5.4343,[2]3.8996,[3]3.8149,[4]4.2813,[5]4.7551,[6]4.8896,[7]4.3971,[8]4.8784,[9]5.0628,
+save_imatrix: stored collected data after 10 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[10]5.3943,[11]5.4217,[12]5.0285,[13]4.9134,[14]5.1438,[15]5.5571,[16]5.6656,[17]5.9607,[18]6.1181,[19]6.2656,
+save_imatrix: stored collected data after 20 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[20]6.3909,[21]6.6078,[22]6.3513,[23]6.0687,[24]6.1444,[25]6.2039,[26]6.0961,[27]5.9920,[28]6.0692,[29]6.2414,
+save_imatrix: stored collected data after 30 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[30]6.3627,[31]6.3409,[32]6.4753,[33]6.5867,[34]6.7751,[35]6.7987,[36]6.8239,[37]6.5432,[38]6.3571,[39]6.2625,
+save_imatrix: stored collected data after 40 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[40]6.1535,[41]6.0799,[42]6.0834,[43]6.0280,[44]6.0363,[45]5.9998,[46]5.9587,[47]5.9597,[48]6.0238,[49]6.1117,
+save_imatrix: stored collected data after 50 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[50]6.1246,[51]6.3047,[52]6.4659,[53]6.6468,[54]6.8254,[55]6.9231,[56]6.8431,[57]6.7428,[58]6.7578,[59]6.8111,
+save_imatrix: stored collected data after 60 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[60]6.9017,[61]6.7848,[62]6.7904,[63]6.8443,[64]6.9221,[65]6.9817,[66]7.0156,[67]7.0694,[68]7.1127,[69]7.0954,
+save_imatrix: stored collected data after 70 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[70]7.1040,[71]7.0925,[72]7.1185,[73]7.0637,[74]6.9930,[75]6.9701,[76]7.0329,[77]7.0270,[78]6.9920,[79]6.9800,
+save_imatrix: stored collected data after 80 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[80]6.9818,[81]6.9469,[82]6.9240,[83]6.8928,[84]6.8914,[85]6.8941,[86]6.8804,[87]6.8794,[88]6.8692,[89]6.8521,
+save_imatrix: stored collected data after 90 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[90]6.8342,[91]6.8410,[92]6.8011,[93]6.7910,[94]6.7614,[95]6.7156,[96]6.7232,[97]6.7062,[98]6.7103,[99]6.6828,
+save_imatrix: stored collected data after 100 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[100]6.6730,[101]6.6802,[102]6.6431,[103]6.6045,[104]6.5952,[105]6.6153,[106]6.6126,[107]6.6340,[108]6.6482,[109]6.6071,
+save_imatrix: stored collected data after 110 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[110]6.5626,[111]6.5220,[112]6.4816,[113]6.4386,[114]6.3930,[115]6.3538,[116]6.3223,[117]6.2917,[118]6.3010,[119]6.3069,
+save_imatrix: stored collected data after 120 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[120]6.3563,[121]6.4052,[122]6.4605,[123]6.5090,[124]6.5836,[125]6.6534,[126]6.6648,[127]6.6721,[128]6.6135,[129]6.6104,
+save_imatrix: stored collected data after 130 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[130]6.5800,[131]6.5530,[132]6.5075,[133]6.4591,[134]6.4719,[135]6.4909,[136]6.4868,[137]6.4848,[138]6.4945,[139]6.5073,
+save_imatrix: stored collected data after 140 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[140]6.5218,[141]6.5243,[142]6.5266,[143]6.5127,[144]6.4885,[145]6.5051,[146]6.5372,[147]6.5788,[148]6.6177,[149]6.6584,
+save_imatrix: stored collected data after 150 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+[150]6.6965,[151]6.7404,
+save_imatrix: stored collected data after 151 chunks in Phi-3-mini-4k-instruct-IMat-GGUF/imatrix.dat
+
+llama_print_timings:        load time =    1141.39 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 =   41002.68 ms / 77312 tokens (    0.53 ms per token,  1885.54 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 =   42175.96 ms / 77313 tokens
+
+Final estimate: PPL = 6.7404 +/- 0.08396