llama_model_loader: loaded meta data with 34 key-value pairs and 723 tensors from Reflection-Llama-3.1-70B-IMat-GGUF/Reflection-Llama-3.1-70B.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              = Meta Llama 3 70B Instruct
llama_model_loader: - kv   3:                       general.organization str              = Meta Llama
llama_model_loader: - kv   4:                           general.finetune str              = Instruct
llama_model_loader: - kv   5:                           general.basename str              = Meta-Llama-3
llama_model_loader: - kv   6:                         general.size_label str              = 70B
llama_model_loader: - kv   7:                            general.license str              = llama3.1
llama_model_loader: - kv   8:                   general.base_model.count u32              = 1
llama_model_loader: - kv   9:                  general.base_model.0.name str              = Meta Llama 3.1 70B Instruct
llama_model_loader: - kv  10:          general.base_model.0.organization str              = Meta Llama
llama_model_loader: - kv  11:              general.base_model.0.repo_url str              = https://huggingface.co/meta-llama/Met...
llama_model_loader: - kv  12:                               general.tags arr[str,1]       = ["text-generation"]
llama_model_loader: - kv  13:                          llama.block_count u32              = 80
llama_model_loader: - kv  14:                       llama.context_length u32              = 8192
llama_model_loader: - kv  15:                     llama.embedding_length u32              = 8192
llama_model_loader: - kv  16:                  llama.feed_forward_length u32              = 28672
llama_model_loader: - kv  17:                 llama.attention.head_count u32              = 64
llama_model_loader: - kv  18:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv  19:                       llama.rope.freq_base f32              = 500000.000000
llama_model_loader: - kv  20:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  21:                          general.file_type u32              = 7
llama_model_loader: - kv  22:                           llama.vocab_size u32              = 128262
llama_model_loader: - kv  23:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  24:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  25:                         tokenizer.ggml.pre str              = llama-bpe
llama_model_loader: - kv  26:                      tokenizer.ggml.tokens arr[str,128262]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  27:                  tokenizer.ggml.token_type arr[i32,128262]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  28:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv  29:                tokenizer.ggml.bos_token_id u32              = 128000
llama_model_loader: - kv  30:                tokenizer.ggml.eos_token_id u32              = 128009
llama_model_loader: - kv  31:            tokenizer.ggml.padding_token_id u32              = 128009
llama_model_loader: - kv  32:                    tokenizer.chat_template str              = {% set loop_messages = messages %}{% ...
llama_model_loader: - kv  33:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  161 tensors
llama_model_loader: - type q8_0:  562 tensors
llm_load_vocab: special tokens cache size = 262
llm_load_vocab: token to piece cache size = 0.8000 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = llama
llm_load_print_meta: vocab type       = BPE
llm_load_print_meta: n_vocab          = 128262
llm_load_print_meta: n_merges         = 280147
llm_load_print_meta: vocab_only       = 0
llm_load_print_meta: n_ctx_train      = 8192
llm_load_print_meta: n_embd           = 8192
llm_load_print_meta: n_layer          = 80
llm_load_print_meta: n_head           = 64
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            = 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-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             = 28672
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  = 500000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn  = 8192
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       = 70B
llm_load_print_meta: model ftype      = Q8_0
llm_load_print_meta: model params     = 70.55 B
llm_load_print_meta: model size       = 69.82 GiB (8.50 BPW) 
llm_load_print_meta: general.name     = Meta Llama 3 70B Instruct
llm_load_print_meta: BOS token        = 128000 '<|begin_of_text|>'
llm_load_print_meta: EOS token        = 128009 '<|eot_id|>'
llm_load_print_meta: PAD token        = 128009 '<|eot_id|>'
llm_load_print_meta: LF token         = 128 'Ä'
llm_load_print_meta: EOT token        = 128009 '<|eot_id|>'
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 =    0.68 MiB
llm_load_tensors: offloading 25 repeating layers to GPU
llm_load_tensors: offloaded 25/81 layers to GPU
llm_load_tensors:        CPU buffer size = 71494.38 MiB
llm_load_tensors:      CUDA0 buffer size = 21676.56 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  = 500000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init:  CUDA_Host KV buffer size =   110.00 MiB
llama_kv_cache_init:      CUDA0 KV buffer size =    50.00 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 =     0.49 MiB
llama_new_context_with_model:      CUDA0 compute buffer size =  1331.19 MiB
llama_new_context_with_model:  CUDA_Host compute buffer size =    17.01 MiB
llama_new_context_with_model: graph nodes  = 2566
llama_new_context_with_model: graph splits = 609

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 43.174 ms
compute_imatrix: computing over 125 chunks with batch_size 512
compute_imatrix: 5.89 seconds per pass - ETA 12.25 minutes
[1]5.9985,[2]4.4764,[3]3.8989,[4]4.7385,[5]4.7986,[6]4.0443,[7]4.1299,[8]4.5462,[9]4.8014,
save_imatrix: stored collected data after 10 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[10]4.4081,[11]4.8686,[12]5.3513,[13]5.8343,[14]6.2641,[15]6.5275,[16]6.8746,[17]7.0103,[18]6.7349,[19]6.4256,
save_imatrix: stored collected data after 20 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[20]6.4326,[21]6.5717,[22]6.5525,[23]6.7670,[24]6.7271,[25]7.0591,[26]7.0410,[27]6.6238,[28]6.2935,[29]6.3051,
save_imatrix: stored collected data after 30 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[30]6.2833,[31]5.9767,[32]5.7087,[33]5.5869,[34]5.4917,[35]5.5808,[36]5.6471,[37]5.6256,[38]5.7035,[39]5.8553,
save_imatrix: stored collected data after 40 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[40]5.9525,[41]5.7458,[42]5.5510,[43]5.3823,[44]5.2344,[45]5.2025,[46]5.1741,[47]5.2933,[48]5.3845,[49]5.4845,
save_imatrix: stored collected data after 50 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[50]5.4510,[51]5.5448,[52]5.6486,[53]5.7359,[54]5.8005,[55]5.8907,[56]5.9464,[57]6.0125,[58]6.0514,[59]6.0705,
save_imatrix: stored collected data after 60 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[60]6.0508,[61]6.0632,[62]6.1140,[63]6.1803,[64]6.1305,[65]6.1261,[66]6.1501,[67]6.1475,[68]6.1542,[69]6.1526,
save_imatrix: stored collected data after 70 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[70]6.1726,[71]6.1811,[72]6.2016,[73]6.1905,[74]6.1620,[75]6.1710,[76]6.1825,[77]6.1710,[78]6.1771,[79]6.2167,
save_imatrix: stored collected data after 80 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[80]6.2429,[81]6.2421,[82]6.2574,[83]6.2922,[84]6.2218,[85]6.2174,[86]6.2301,[87]6.2520,[88]6.2912,[89]6.3056,
save_imatrix: stored collected data after 90 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[90]6.2753,[91]6.2366,[92]6.1995,[93]6.1766,[94]6.1462,[95]6.1181,[96]6.0893,[97]6.1151,[98]6.1628,[99]6.2287,
save_imatrix: stored collected data after 100 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[100]6.2908,[101]6.3385,[102]6.4423,[103]6.4692,[104]6.5022,[105]6.4584,[106]6.4757,[107]6.4469,[108]6.3831,[109]6.3132,
save_imatrix: stored collected data after 110 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[110]6.3544,[111]6.4023,[112]6.4253,[113]6.4320,[114]6.4691,[115]6.5127,[116]6.5334,[117]6.5611,[118]6.5905,[119]6.5512,
save_imatrix: stored collected data after 120 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat
[120]6.4765,[121]6.3970,[122]6.3229,[123]6.2496,[124]6.2033,[125]6.1428,
save_imatrix: stored collected data after 125 chunks in Reflection-Llama-3.1-70B-IMat-GGUF/imatrix.dat

llama_print_timings:        load time =   28195.97 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 =  697528.68 ms / 64000 tokens (   10.90 ms per token,    91.75 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 =  720919.57 ms / 64001 tokens

Final estimate: PPL = 6.1428 +/- 0.08656