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imatrix.log

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+llama_model_loader: loaded meta data with 29 key-value pairs and 338 tensors from reader-lm-1.5b-IMat-GGUF/reader-lm-1.5b.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.type str              = model
+llama_model_loader: - kv   2:                               general.name str              = Qwen2 1.5b Reader
+llama_model_loader: - kv   3:                       general.organization str              = Jinaai
+llama_model_loader: - kv   4:                           general.finetune str              = reader
+llama_model_loader: - kv   5:                           general.basename str              = qwen2
+llama_model_loader: - kv   6:                         general.size_label str              = 1.5B
+llama_model_loader: - kv   7:                            general.license str              = cc-by-nc-4.0
+llama_model_loader: - kv   8:                               general.tags arr[str,1]       = ["text-generation"]
+llama_model_loader: - kv   9:                          general.languages arr[str,1]       = ["multilingual"]
+llama_model_loader: - kv  10:                          qwen2.block_count u32              = 28
+llama_model_loader: - kv  11:                       qwen2.context_length u32              = 256000
+llama_model_loader: - kv  12:                     qwen2.embedding_length u32              = 1536
+llama_model_loader: - kv  13:                  qwen2.feed_forward_length u32              = 8960
+llama_model_loader: - kv  14:                 qwen2.attention.head_count u32              = 12
+llama_model_loader: - kv  15:              qwen2.attention.head_count_kv u32              = 2
+llama_model_loader: - kv  16:                       qwen2.rope.freq_base f32              = 2000000.000000
+llama_model_loader: - kv  17:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
+llama_model_loader: - kv  18:                          general.file_type u32              = 7
+llama_model_loader: - kv  19:                       tokenizer.ggml.model str              = gpt2
+llama_model_loader: - kv  20:                         tokenizer.ggml.pre str              = qwen2
+llama_model_loader: - kv  21:                      tokenizer.ggml.tokens arr[str,151936]  = ["!", "\"", "#", "$", "%", "&", "'", ...
+llama_model_loader: - kv  22:                  tokenizer.ggml.token_type arr[i32,151936]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
+llama_model_loader: - kv  23:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
+llama_model_loader: - kv  24:                tokenizer.ggml.eos_token_id u32              = 151645
+llama_model_loader: - kv  25:            tokenizer.ggml.padding_token_id u32              = 151643
+llama_model_loader: - kv  26:                tokenizer.ggml.bos_token_id u32              = 151643
+llama_model_loader: - kv  27:                    tokenizer.chat_template str              = {% for message in messages %}{% if lo...
+llama_model_loader: - kv  28:               general.quantization_version u32              = 2
+llama_model_loader: - type  f32:  141 tensors
+llama_model_loader: - type q8_0:  197 tensors
+llm_load_vocab: special tokens cache size = 3
+llm_load_vocab: token to piece cache size = 0.9308 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          = 151936
+llm_load_print_meta: n_merges         = 151387
+llm_load_print_meta: vocab_only       = 0
+llm_load_print_meta: n_ctx_train      = 256000
+llm_load_print_meta: n_embd           = 1536
+llm_load_print_meta: n_layer          = 28
+llm_load_print_meta: n_head           = 12
+llm_load_print_meta: n_head_kv        = 2
+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     = 256
+llm_load_print_meta: n_embd_v_gqa     = 256
+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             = 8960
+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  = 2000000.0
+llm_load_print_meta: freq_scale_train = 1
+llm_load_print_meta: n_ctx_orig_yarn  = 256000
+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     = 1.54 B
+llm_load_print_meta: model size       = 1.53 GiB (8.50 BPW) 
+llm_load_print_meta: general.name     = Qwen2 1.5b Reader
+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|>'
+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 =    0.30 MiB
+llm_load_tensors: offloading 28 repeating layers to GPU
+llm_load_tensors: offloading non-repeating layers to GPU
+llm_load_tensors: offloaded 29/29 layers to GPU
+llm_load_tensors:        CPU buffer size =   236.47 MiB
+llm_load_tensors:      CUDA0 buffer size =  1564.63 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  = 2000000.0
+llama_new_context_with_model: freq_scale = 1
+llama_kv_cache_init:      CUDA0 KV buffer size =    14.00 MiB
+llama_new_context_with_model: KV self size  =   14.00 MiB, K (f16):    7.00 MiB, V (f16):    7.00 MiB
+llama_new_context_with_model:  CUDA_Host  output buffer size =     0.58 MiB
+llama_new_context_with_model:      CUDA0 compute buffer size =   299.75 MiB
+llama_new_context_with_model:  CUDA_Host compute buffer size =     4.01 MiB
+llama_new_context_with_model: graph nodes  = 986
+llama_new_context_with_model: graph splits = 2
+
+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 | 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 128.746 ms
+compute_imatrix: computing over 128 chunks with batch_size 512
+compute_imatrix: 0.38 seconds per pass - ETA 0.82 minutes
+[1]9.2771,[2]6.8644,[3]6.4782,[4]7.4881,[5]7.2917,[6]6.6791,[7]7.3505,[8]7.7499,[9]8.4398,
+save_imatrix: stored collected data after 10 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[10]7.9031,[11]7.7003,[12]8.2857,[13]9.0872,[14]9.3184,[15]10.0522,[16]10.4603,[17]10.5844,[18]11.0963,[19]10.6325,
+save_imatrix: stored collected data after 20 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[20]10.6879,[21]10.7507,[22]10.7492,[23]10.6613,[24]10.9654,[25]11.0832,[26]11.0748,[27]11.4078,[28]11.6878,[29]12.1242,
+save_imatrix: stored collected data after 30 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[30]12.0099,[31]11.7409,[32]11.2796,[33]10.9901,[34]10.8007,[35]10.5697,[36]10.5644,[37]10.6097,[38]10.7267,[39]10.7439,
+save_imatrix: stored collected data after 40 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[40]10.9118,[41]10.9510,[42]11.4185,[43]11.8320,[44]12.2346,[45]12.5533,[46]12.7154,[47]12.5249,[48]12.5437,[49]12.6274,
+save_imatrix: stored collected data after 50 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[50]12.6882,[51]12.5225,[52]12.6191,[53]12.8579,[54]12.9677,[55]13.1179,[56]13.1808,[57]13.1997,[58]13.2493,[59]13.2682,
+save_imatrix: stored collected data after 60 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[60]13.2639,[61]13.1555,[62]13.0986,[63]13.1404,[64]13.2389,[65]13.1620,[66]13.1591,[67]13.1465,[68]13.0630,[69]13.0219,
+save_imatrix: stored collected data after 70 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[70]12.9859,[71]12.9325,[72]12.9059,[73]12.9107,[74]12.7811,[75]12.6892,[76]12.5848,[77]12.5441,[78]12.5483,[79]12.5050,
+save_imatrix: stored collected data after 80 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[80]12.4548,[81]12.4615,[82]12.4451,[83]12.3640,[84]12.4103,[85]12.4209,[86]12.3428,[87]12.2794,[88]12.2333,[89]12.2637,
+save_imatrix: stored collected data after 90 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[90]12.2632,[91]12.2392,[92]12.1162,[93]12.0106,[94]11.8707,[95]11.7481,[96]11.6479,[97]11.5368,[98]11.4347,[99]11.3816,
+save_imatrix: stored collected data after 100 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[100]11.3768,[101]11.3839,[102]11.5189,[103]11.6346,[104]11.7308,[105]11.9020,[106]11.9952,[107]12.0287,[108]11.9878,[109]11.9411,
+save_imatrix: stored collected data after 110 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[110]11.9535,[111]11.9408,[112]11.8850,[113]11.9203,[114]11.9687,[115]11.9471,[116]11.9409,[117]11.9471,[118]11.9818,[119]11.9618,
+save_imatrix: stored collected data after 120 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+[120]11.9384,[121]11.9241,[122]11.8738,[123]11.9322,[124]12.0272,[125]12.1018,[126]12.1950,[127]12.2749,[128]12.3603,
+save_imatrix: stored collected data after 128 chunks in reader-lm-1.5b-IMat-GGUF/imatrix.dat
+
+llama_perf_print:        load time =     926.91 ms
+llama_perf_print: prompt eval time =   30274.30 ms / 65536 tokens (    0.46 ms per token,  2164.74 tokens per second)
+llama_perf_print:        eval time =       0.00 ms /     1 runs   (    0.00 ms per token,      inf tokens per second)
+llama_perf_print:       total time =   31809.38 ms / 65537 tokens
+
+Final estimate: PPL = 12.3603 +/- 0.18881