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+llama_model_loader: loaded meta data with 29 key-value pairs and 290 tensors from reader-lm-0.5b-IMat-GGUF/reader-lm-0.5b.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 0.5b 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              = 0.5B
+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              = 24
+llama_model_loader: - kv  11:                       qwen2.context_length u32              = 256000
+llama_model_loader: - kv  12:                     qwen2.embedding_length u32              = 896
+llama_model_loader: - kv  13:                  qwen2.feed_forward_length u32              = 4864
+llama_model_loader: - kv  14:                 qwen2.attention.head_count u32              = 14
+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:  121 tensors
+llama_model_loader: - type q8_0:  169 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           = 896
+llm_load_print_meta: n_layer          = 24
+llm_load_print_meta: n_head           = 14
+llm_load_print_meta: n_head_kv        = 2
+llm_load_print_meta: n_rot            = 64
+llm_load_print_meta: n_swa            = 0
+llm_load_print_meta: n_embd_head_k    = 64
+llm_load_print_meta: n_embd_head_v    = 64
+llm_load_print_meta: n_gqa            = 7
+llm_load_print_meta: n_embd_k_gqa     = 128
+llm_load_print_meta: n_embd_v_gqa     = 128
+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             = 4864
+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       = 1B
+llm_load_print_meta: model ftype      = Q8_0
+llm_load_print_meta: model params     = 494.03 M
+llm_load_print_meta: model size       = 500.79 MiB (8.50 BPW)
+llm_load_print_meta: general.name     = Qwen2 0.5b 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 =    0.25 MiB
+llm_load_tensors: offloading 24 repeating layers to GPU
+llm_load_tensors: offloading non-repeating layers to GPU
+llm_load_tensors: offloaded 25/25 layers to GPU
+llm_load_tensors:        CPU buffer size =   137.94 MiB
+llm_load_tensors:      CUDA0 buffer size =   500.84 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 =     6.00 MiB
+llama_new_context_with_model: KV self size  =    6.00 MiB, K (f16):    3.00 MiB, V (f16):    3.00 MiB
+llama_new_context_with_model:  CUDA_Host  output buffer size =     0.58 MiB
+llama_new_context_with_model:      CUDA0 compute buffer size =   298.50 MiB
+llama_new_context_with_model:  CUDA_Host compute buffer size =     2.76 MiB
+llama_new_context_with_model: graph nodes  = 846
+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 135.191 ms
+compute_imatrix: computing over 128 chunks with batch_size 512
+compute_imatrix: 0.31 seconds per pass - ETA 0.67 minutes
+[1]17.5855,[2]30.5654,[3]24.3179,[4]23.8257,[5]28.3527,[6]23.2434,[7]23.5053,[8]27.3149,[9]26.8703,
+save_imatrix: stored collected data after 10 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[10]22.9816,[11]20.9238,[12]21.3352,[13]24.0195,[14]25.3831,[15]26.3731,[16]26.5095,[17]25.8473,[18]28.2340,[19]27.2074,
+save_imatrix: stored collected data after 20 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[20]26.4319,[21]26.1346,[22]25.6698,[23]26.5493,[24]28.6411,[25]30.0712,[26]29.5481,[27]31.1370,[28]31.3748,[29]31.8980,
+save_imatrix: stored collected data after 30 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[30]33.4559,[31]32.5650,[32]31.4434,[33]30.9599,[34]30.5894,[35]29.5064,[36]29.1429,[37]30.0905,[38]29.9891,[39]30.7946,
+save_imatrix: stored collected data after 40 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[40]30.7759,[41]31.4073,[42]33.0237,[43]33.7226,[44]34.4842,[45]34.9874,[46]35.1861,[47]34.3317,[48]34.6818,[49]34.6933,
+save_imatrix: stored collected data after 50 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[50]35.2924,[51]34.6092,[52]35.2739,[53]35.5858,[54]35.5820,[55]36.6457,[56]37.5340,[57]37.9605,[58]38.5727,[59]39.0046,
+save_imatrix: stored collected data after 60 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[60]38.4983,[61]37.9428,[62]37.4100,[63]37.1360,[64]38.0599,[65]37.5736,[66]37.8492,[67]38.0620,[68]37.5754,[69]37.2230,
+save_imatrix: stored collected data after 70 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[70]36.9500,[71]36.4919,[72]36.6494,[73]37.1150,[74]36.8300,[75]36.2223,[76]36.1447,[77]36.1864,[78]36.4957,[79]36.8705,
+save_imatrix: stored collected data after 80 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[80]36.4471,[81]36.7004,[82]36.3808,[83]35.8913,[84]36.3684,[85]36.1145,[86]35.6615,[87]35.1692,[88]35.3073,[89]36.0478,
+save_imatrix: stored collected data after 90 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[90]35.8692,[91]36.1951,[92]35.4915,[93]35.2934,[94]34.7298,[95]34.0772,[96]33.5280,[97]33.1758,[98]32.6341,[99]33.0392,
+save_imatrix: stored collected data after 100 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[100]32.8555,[101]32.6738,[102]33.3807,[103]33.5267,[104]33.6360,[105]34.2168,[106]34.2754,[107]34.1549,[108]34.4034,[109]34.5580,
+save_imatrix: stored collected data after 110 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[110]34.4285,[111]34.1185,[112]33.7908,[113]33.6723,[114]33.5806,[115]33.3842,[116]33.6631,[117]33.7834,[118]33.6583,[119]33.6815,
+save_imatrix: stored collected data after 120 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+[120]33.3917,[121]33.2004,[122]32.9209,[123]33.1892,[124]33.3031,[125]33.4261,[126]33.8849,[127]34.0284,[128]34.1452,
+save_imatrix: stored collected data after 128 chunks in reader-lm-0.5b-IMat-GGUF/imatrix.dat
+llama_perf_print:        load time =     716.69 ms
+llama_perf_print: prompt eval time =   17498.94 ms / 65536 tokens (    0.27 ms per token,  3745.14 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 =   18830.03 ms / 65537 tokens
+Final estimate: PPL = 34.1452 +/- 0.62968