File size: 12,000 Bytes
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main: build = 2998 (9588f196)
main: built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
main: seed = 1716669278
llama_model_loader: loaded meta data with 28 key-value pairs and 258 tensors from aya-23-8B-IMat-GGUF/aya-23-8B.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 = command-r
llama_model_loader: - kv 1: general.name str = aya-23-8B
llama_model_loader: - kv 2: command-r.block_count u32 = 32
llama_model_loader: - kv 3: command-r.context_length u32 = 8192
llama_model_loader: - kv 4: command-r.embedding_length u32 = 4096
llama_model_loader: - kv 5: command-r.feed_forward_length u32 = 14336
llama_model_loader: - kv 6: command-r.attention.head_count u32 = 32
llama_model_loader: - kv 7: command-r.attention.head_count_kv u32 = 8
llama_model_loader: - kv 8: command-r.rope.freq_base f32 = 10000.000000
llama_model_loader: - kv 9: command-r.attention.layer_norm_epsilon f32 = 0.000010
llama_model_loader: - kv 10: general.file_type u32 = 1
llama_model_loader: - kv 11: command-r.logit_scale f32 = 0.062500
llama_model_loader: - kv 12: command-r.rope.scaling.type str = none
llama_model_loader: - kv 13: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 14: tokenizer.ggml.pre str = command-r
llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,256000] = ["<PAD>", "<UNK>", "<CLS>", "<SEP>", ...
llama_model_loader: - kv 16: tokenizer.ggml.token_type arr[i32,256000] = [3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, ...
llama_model_loader: - kv 17: tokenizer.ggml.merges arr[str,253333] = ["Ġ Ġ", "Ġ t", "e r", "i n", "Ġ a...
llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 5
llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 255001
llama_model_loader: - kv 20: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - kv 21: tokenizer.ggml.add_bos_token bool = true
llama_model_loader: - kv 22: tokenizer.ggml.add_eos_token bool = false
llama_model_loader: - kv 23: tokenizer.chat_template.tool_use str = {{ bos_token }}{% if messages[0]['rol...
llama_model_loader: - kv 24: tokenizer.chat_template.rag str = {{ bos_token }}{% if messages[0]['rol...
llama_model_loader: - kv 25: tokenizer.chat_templates arr[str,2] = ["tool_use", "rag"]
llama_model_loader: - kv 26: tokenizer.chat_template str = {{ bos_token }}{% if messages[0]['rol...
llama_model_loader: - kv 27: general.quantization_version u32 = 2
llama_model_loader: - type f32: 33 tensors
llama_model_loader: - type f16: 225 tensors
llm_load_vocab: special tokens definition check successful ( 1008/256000 ).
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = command-r
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 256000
llm_load_print_meta: n_merges = 253333
llm_load_print_meta: n_ctx_train = 8192
llm_load_print_meta: n_embd = 4096
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_layer = 32
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 = 4
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 = 1.0e-05
llm_load_print_meta: f_norm_rms_eps = 0.0e+00
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 = 6.2e-02
llm_load_print_meta: n_ff = 14336
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 = none
llm_load_print_meta: freq_base_train = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx = 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: model type = ?B
llm_load_print_meta: model ftype = F16
llm_load_print_meta: model params = 8.03 B
llm_load_print_meta: model size = 14.95 GiB (16.00 BPW)
llm_load_print_meta: general.name = aya-23-8B
llm_load_print_meta: BOS token = 5 '<BOS_TOKEN>'
llm_load_print_meta: EOS token = 255001 '<|END_OF_TURN_TOKEN|>'
llm_load_print_meta: PAD token = 0 '<PAD>'
llm_load_print_meta: LF token = 136 'Ä'
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 = 0.27 MiB
llm_load_tensors: offloading 20 repeating layers to GPU
llm_load_tensors: offloaded 20/33 layers to GPU
llm_load_tensors: CPU buffer size = 15312.52 MiB
llm_load_tensors: CUDA0 buffer size = 8320.31 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: CUDA_Host KV buffer size = 24.00 MiB
llama_kv_cache_init: CUDA0 KV buffer size = 40.00 MiB
llama_new_context_with_model: KV self size = 64.00 MiB, K (f16): 32.00 MiB, V (f16): 32.00 MiB
llama_new_context_with_model: CUDA_Host output buffer size = 0.98 MiB
llama_new_context_with_model: CUDA0 compute buffer size = 2516.00 MiB
llama_new_context_with_model: CUDA_Host compute buffer size = 9.01 MiB
llama_new_context_with_model: graph nodes = 968
llama_new_context_with_model: graph splits = 124
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 187.854 ms
compute_imatrix: computing over 194 chunks with batch_size 512
compute_imatrix: 0.91 seconds per pass - ETA 2.92 minutes
[1]7.1190,[2]4.7963,[3]4.6059,[4]5.2739,[5]5.1456,[6]4.7816,[7]5.7129,[8]6.0872,[9]6.7418,
save_imatrix: stored collected data after 10 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[10]7.0130,[11]7.1909,[12]7.3099,[13]7.7753,[14]7.9571,[15]8.3000,[16]8.5210,[17]8.6988,[18]8.9548,[19]9.0360,
save_imatrix: stored collected data after 20 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[20]8.6010,[21]8.3664,[22]8.1867,[23]7.7215,[24]7.4229,[25]7.3781,[26]7.5362,[27]7.4628,[28]7.6019,[29]7.4947,
save_imatrix: stored collected data after 30 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[30]7.5277,[31]7.1883,[32]7.0002,[33]6.9088,[34]6.8530,[35]6.8045,[36]6.8115,[37]6.8715,[38]6.9325,[39]7.0417,
save_imatrix: stored collected data after 40 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[40]7.1304,[41]7.2202,[42]7.4146,[43]7.6280,[44]7.8621,[45]7.9827,[46]7.9802,[47]7.9503,[48]7.8607,[49]7.9686,
save_imatrix: stored collected data after 50 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[50]8.0385,[51]8.1188,[52]8.2639,[53]8.3293,[54]8.4304,[55]8.5259,[56]8.5475,[57]8.5795,[58]8.6124,[59]8.6107,
save_imatrix: stored collected data after 60 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[60]8.7115,[61]8.8002,[62]8.8682,[63]8.9158,[64]8.8321,[65]8.8011,[66]8.7690,[67]8.7664,[68]8.7518,[69]8.7095,
save_imatrix: stored collected data after 70 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[70]8.6180,[71]8.5990,[72]8.5778,[73]8.5959,[74]8.6055,[75]8.6153,[76]8.6184,[77]8.6011,[78]8.5432,[79]8.5512,
save_imatrix: stored collected data after 80 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[80]8.5401,[81]8.5431,[82]8.5836,[83]8.5824,[84]8.6061,[85]8.6119,[86]8.5804,[87]8.5612,[88]8.5708,[89]8.5804,
save_imatrix: stored collected data after 90 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[90]8.5891,[91]8.5533,[92]8.4998,[93]8.4785,[94]8.4974,[95]8.4786,[96]8.4704,[97]8.4801,[98]8.5061,[99]8.4687,
save_imatrix: stored collected data after 100 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[100]8.4955,[101]8.4923,[102]8.4611,[103]8.4774,[104]8.4411,[105]8.3941,[106]8.3383,[107]8.3762,[108]8.4215,[109]8.4042,
save_imatrix: stored collected data after 110 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[110]8.3948,[111]8.3834,[112]8.4448,[113]8.3678,[114]8.3469,[115]8.3120,[116]8.2475,[117]8.2068,[118]8.1588,[119]8.1061,
save_imatrix: stored collected data after 120 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[120]8.0583,[121]8.0006,[122]7.9571,[123]7.9071,[124]7.8589,[125]7.8224,[126]7.8380,[127]7.8673,[128]7.8994,[129]7.9217,
save_imatrix: stored collected data after 130 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[130]7.9478,[131]8.0433,[132]8.1334,[133]8.2221,[134]8.3227,[135]8.3720,[136]8.4199,[137]8.4348,[138]8.4647,[139]8.4751,
save_imatrix: stored collected data after 140 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[140]8.4985,[141]8.5340,[142]8.5555,[143]8.5847,[144]8.6165,[145]8.6354,[146]8.6218,[147]8.6620,[148]8.6799,[149]8.6998,
save_imatrix: stored collected data after 150 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[150]8.6752,[151]8.7044,[152]8.6958,[153]8.6653,[154]8.6468,[155]8.6413,[156]8.6339,[157]8.6284,[158]8.6294,[159]8.5902,
save_imatrix: stored collected data after 160 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[160]8.6397,[161]8.6918,[162]8.7399,[163]8.8271,[164]8.8731,[165]8.8877,[166]8.8902,[167]8.9293,[168]8.9149,[169]8.9450,
save_imatrix: stored collected data after 170 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[170]8.9197,[171]8.9054,[172]8.9088,[173]8.9341,[174]8.9329,[175]8.9375,[176]8.9496,[177]8.9887,[178]9.0170,[179]9.0041,
save_imatrix: stored collected data after 180 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[180]9.0067,[181]8.9939,[182]8.9932,[183]8.9789,[184]8.9741,[185]8.9363,[186]8.9414,[187]8.9221,[188]8.9945,[189]9.0665,
save_imatrix: stored collected data after 190 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
[190]9.1200,[191]9.1653,[192]9.1639,[193]9.1284,[194]9.0943,
save_imatrix: stored collected data after 194 chunks in aya-23-8B-IMat-GGUF/imatrix.dat
llama_print_timings: load time = 2130.43 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 = 152430.74 ms / 99328 tokens ( 1.53 ms per token, 651.63 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 = 155917.19 ms / 99329 tokens
Final estimate: PPL = 9.0943 +/- 0.10864
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