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imatrix.log

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+llama_model_loader: loaded meta data with 21 key-value pairs and 963 tensors from Qwen2-72B-Instruct-IMat-GGUF/Qwen2-72B-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              = qwen2
+llama_model_loader: - kv   1:                               general.name str              = Qwen2-72B-Instruct
+llama_model_loader: - kv   2:                          qwen2.block_count u32              = 80
+llama_model_loader: - kv   3:                       qwen2.context_length u32              = 32768
+llama_model_loader: - kv   4:                     qwen2.embedding_length u32              = 8192
+llama_model_loader: - kv   5:                  qwen2.feed_forward_length u32              = 29568
+llama_model_loader: - kv   6:                 qwen2.attention.head_count u32              = 64
+llama_model_loader: - kv   7:              qwen2.attention.head_count_kv u32              = 8
+llama_model_loader: - kv   8:                       qwen2.rope.freq_base f32              = 1000000.000000
+llama_model_loader: - kv   9:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
+llama_model_loader: - kv  10:                          general.file_type u32              = 7
+llama_model_loader: - kv  11:                       tokenizer.ggml.model str              = gpt2
+llama_model_loader: - kv  12:                         tokenizer.ggml.pre str              = qwen2
+llama_model_loader: - kv  13:                      tokenizer.ggml.tokens arr[str,152064]  = ["!", "\"", "#", "$", "%", "&", "'", ...
+llama_model_loader: - kv  14:                  tokenizer.ggml.token_type arr[i32,152064]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
+llama_model_loader: - kv  15:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
+llama_model_loader: - kv  16:                tokenizer.ggml.eos_token_id u32              = 151645
+llama_model_loader: - kv  17:            tokenizer.ggml.padding_token_id u32              = 151643
+llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 151643
+llama_model_loader: - kv  19:                    tokenizer.chat_template str              = {% for message in messages %}{% if lo...
+llama_model_loader: - kv  20:               general.quantization_version u32              = 2
+llama_model_loader: - type  f32:  401 tensors
+llama_model_loader: - type q8_0:  562 tensors
+llm_load_vocab: special tokens cache size = 421
+llm_load_vocab: token to piece cache size = 0.9352 MB
+llm_load_print_meta: format           = GGUF V3 (latest)
+llm_load_print_meta: arch             = qwen2
+llm_load_print_meta: vocab type       = BPE
+llm_load_print_meta: n_vocab          = 152064
+llm_load_print_meta: n_merges         = 151387
+llm_load_print_meta: n_ctx_train      = 32768
+llm_load_print_meta: n_embd           = 8192
+llm_load_print_meta: n_head           = 64
+llm_load_print_meta: n_head_kv        = 8
+llm_load_print_meta: n_layer          = 80
+llm_load_print_meta: n_rot            = 128
+llm_load_print_meta: n_embd_head_k    = 128
+llm_load_print_meta: n_embd_head_v    = 128
+llm_load_print_meta: n_gqa            = 8
+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-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             = 29568
+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  = 1000000.0
+llm_load_print_meta: freq_scale_train = 1
+llm_load_print_meta: n_ctx_orig_yarn  = 32768
+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       = 70B
+llm_load_print_meta: model ftype      = Q8_0
+llm_load_print_meta: model params     = 72.71 B
+llm_load_print_meta: model size       = 71.95 GiB (8.50 BPW) 
+llm_load_print_meta: general.name     = Qwen2-72B-Instruct
+llm_load_print_meta: BOS token        = 151643 '<|endoftext|>'
+llm_load_print_meta: EOS token        = 151645 '<|im_end|>'
+llm_load_print_meta: PAD token        = 151643 '<|endoftext|>'
+llm_load_print_meta: LF token         = 148848 'ÄĬ'
+llm_load_print_meta: EOT token        = 151645 '<|im_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 =    0.92 MiB
+llm_load_tensors: offloading 20 repeating layers to GPU
+llm_load_tensors: offloaded 20/81 layers to GPU
+llm_load_tensors:        CPU buffer size = 73677.66 MiB
+llm_load_tensors:      CUDA0 buffer size = 17788.29 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 =   120.00 MiB
+llama_kv_cache_init:      CUDA0 KV buffer size =    40.00 MiB
+llama_new_context_with_model: KV self size  =  160.00 MiB, K (f16):   80.00 MiB, V (f16):   80.00 MiB
+llama_new_context_with_model:  CUDA_Host  output buffer size =     0.58 MiB
+llama_new_context_with_model:      CUDA0 compute buffer size =  1575.25 MiB
+llama_new_context_with_model:  CUDA_Host compute buffer size =    17.01 MiB
+llama_new_context_with_model: graph nodes  = 2806
+llama_new_context_with_model: graph splits = 844
+
+system_info: n_threads = 32 / 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 136.611 ms
+compute_imatrix: computing over 128 chunks with batch_size 512
+compute_imatrix: 27.81 seconds per pass - ETA 59.32 minutes
+[1]4.0667,[2]2.9968,[3]2.7877,[4]3.0396,[5]3.0193,[6]2.7974,[7]2.9432,[8]3.0042,[9]3.3837,
+save_imatrix: stored collected data after 10 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[10]3.3551,[11]3.3012,[12]3.6225,[13]3.9980,[14]4.2226,[15]4.5451,[16]4.8045,[17]4.9530,[18]5.1710,[19]5.0171,
+save_imatrix: stored collected data after 20 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[20]5.1555,[21]5.1434,[22]5.1624,[23]5.1016,[24]5.2596,[25]5.3729,[26]5.2817,[27]5.3150,[28]5.3345,[29]5.4403,
+save_imatrix: stored collected data after 30 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[30]5.3995,[31]5.2560,[32]5.0742,[33]4.9801,[34]4.9146,[35]4.8823,[36]4.8909,[37]4.9080,[38]4.9352,[39]4.9022,
+save_imatrix: stored collected data after 40 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[40]5.0046,[41]5.0428,[42]5.1636,[43]5.0551,[44]5.1610,[45]5.2157,[46]5.2933,[47]5.2076,[48]5.2499,[49]5.3324,
+save_imatrix: stored collected data after 50 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[50]5.3917,[51]5.3295,[52]5.4023,[53]5.4976,[54]5.5736,[55]5.6064,[56]5.6562,[57]5.6968,[58]5.7409,[59]5.7721,
+save_imatrix: stored collected data after 60 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[60]5.7922,[61]5.7742,[62]5.7481,[63]5.7837,[64]5.8379,[65]5.8041,[66]5.8132,[67]5.8367,[68]5.7894,[69]5.7512,
+save_imatrix: stored collected data after 70 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[70]5.7483,[71]5.7360,[72]5.7379,[73]5.7505,[74]5.7101,[75]5.6809,[76]5.6496,[77]5.6416,[78]5.6378,[79]5.6251,
+save_imatrix: stored collected data after 80 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[80]5.5726,[81]5.6016,[82]5.6046,[83]5.5769,[84]5.5958,[85]5.6151,[86]5.5989,[87]5.5806,[88]5.5546,[89]5.5692,
+save_imatrix: stored collected data after 90 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[90]5.5935,[91]5.5874,[92]5.5595,[93]5.5326,[94]5.4937,[95]5.4613,[96]5.4304,[97]5.3971,[98]5.3679,[99]5.3492,
+save_imatrix: stored collected data after 100 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[100]5.3608,[101]5.3831,[102]5.4434,[103]5.5090,[104]5.5541,[105]5.6454,[106]5.6999,[107]5.7232,[108]5.7158,[109]5.7137,
+save_imatrix: stored collected data after 110 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[110]5.7052,[111]5.6696,[112]5.6187,[113]5.5809,[114]5.6217,[115]5.6262,[116]5.6315,[117]5.6514,[118]5.6844,[119]5.6896,
+save_imatrix: stored collected data after 120 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+[120]5.6892,[121]5.7048,[122]5.6845,[123]5.7023,[124]5.7156,[125]5.7275,[126]5.7575,[127]5.7766,[128]5.8007,
+save_imatrix: stored collected data after 128 chunks in Qwen2-72B-Instruct-IMat-GGUF/imatrix.dat
+
+llama_print_timings:        load time =   74513.74 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 = 1161436.60 ms / 65536 tokens (   17.72 ms per token,    56.43 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 = 1210188.40 ms / 65537 tokens
+
+Final estimate: PPL = 5.8007 +/- 0.07472