llama_model_loader: loaded meta data with 24 key-value pairs and 291 tensors from llm-compiler-7b-IMat-GGUF/llm-compiler-7b.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.name str              = llm-compiler-7b
llama_model_loader: - kv   2:                          llama.block_count u32              = 32
llama_model_loader: - kv   3:                       llama.context_length u32              = 16384
llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 11008
llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 32
llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                          general.file_type u32              = 7
llama_model_loader: - kv  11:                           llama.vocab_size u32              = 32000
llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = default
llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,32000]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv  16:                      tokenizer.ggml.scores arr[f32,32000]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  17:                  tokenizer.ggml.token_type arr[i32,32000]   = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  20:            tokenizer.ggml.unknown_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:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q8_0:  226 tensors
llm_load_vocab: special tokens cache size = 259
llm_load_vocab: token to piece cache size = 0.1684 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = llama
llm_load_print_meta: vocab type       = SPM
llm_load_print_meta: n_vocab          = 32000
llm_load_print_meta: n_merges         = 0
llm_load_print_meta: n_ctx_train      = 16384
llm_load_print_meta: n_embd           = 4096
llm_load_print_meta: n_head           = 32
llm_load_print_meta: n_head_kv        = 32
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            = 1
llm_load_print_meta: n_embd_k_gqa     = 4096
llm_load_print_meta: n_embd_v_gqa     = 4096
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             = 11008
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  = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn  = 16384
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       = 7B
llm_load_print_meta: model ftype      = Q8_0
llm_load_print_meta: model params     = 6.74 B
llm_load_print_meta: model size       = 6.67 GiB (8.50 BPW) 
llm_load_print_meta: general.name     = llm-compiler-7b
llm_load_print_meta: BOS token        = 1 '<s>'
llm_load_print_meta: EOS token        = 2 '</s>'
llm_load_print_meta: UNK token        = 0 '<unk>'
llm_load_print_meta: LF token         = 13 '<0x0A>'
llm_load_print_meta: max token length = 48
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 =    0.27 MiB
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU
llm_load_tensors:        CPU buffer size =   132.81 MiB
llm_load_tensors:      CUDA0 buffer size =  6695.84 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  = 1000000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init:      CUDA0 KV buffer size =   256.00 MiB
llama_new_context_with_model: KV self size  =  256.00 MiB, K (f16):  128.00 MiB, V (f16):  128.00 MiB
llama_new_context_with_model:  CUDA_Host  output buffer size =     0.12 MiB
llama_new_context_with_model:      CUDA0 compute buffer size =    70.50 MiB
llama_new_context_with_model:  CUDA_Host compute buffer size =     9.01 MiB
llama_new_context_with_model: graph nodes  = 1030
llama_new_context_with_model: graph splits = 2

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 98.047 ms
compute_imatrix: computing over 151 chunks with batch_size 512
compute_imatrix: 0.59 seconds per pass - ETA 1.47 minutes
[1]6.6836,[2]5.1025,[3]5.0990,[4]6.0509,[5]6.8286,[6]6.9178,[7]6.4531,[8]7.0779,[9]7.2172,
save_imatrix: stored collected data after 10 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[10]7.6626,[11]7.6180,[12]6.7697,[13]6.6368,[14]6.9780,[15]7.4385,[16]7.5302,[17]7.8579,[18]8.0717,[19]8.2099,
save_imatrix: stored collected data after 20 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[20]8.3085,[21]8.5583,[22]8.1441,[23]7.7425,[24]7.8041,[25]7.8916,[26]7.8419,[27]7.6914,[28]7.8043,[29]7.9600,
save_imatrix: stored collected data after 30 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[30]8.0985,[31]8.1050,[32]8.2265,[33]8.3044,[34]8.5184,[35]8.5777,[36]8.4893,[37]8.1221,[38]7.8718,[39]7.7932,
save_imatrix: stored collected data after 40 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[40]7.7251,[41]7.6244,[42]7.5451,[43]7.3857,[44]7.2989,[45]7.2049,[46]7.1984,[47]7.2254,[48]7.2786,[49]7.3786,
save_imatrix: stored collected data after 50 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[50]7.3834,[51]7.5855,[52]7.7687,[53]7.9564,[54]8.1367,[55]8.2275,[56]8.1763,[57]8.1040,[58]8.1407,[59]8.2010,
save_imatrix: stored collected data after 60 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[60]8.2955,[61]8.1878,[62]8.2123,[63]8.2870,[64]8.3726,[65]8.4340,[66]8.4646,[67]8.5276,[68]8.5576,[69]8.5352,
save_imatrix: stored collected data after 70 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[70]8.5404,[71]8.5466,[72]8.4782,[73]8.4271,[74]8.3748,[75]8.3548,[76]8.3520,[77]8.3590,[78]8.3342,[79]8.3392,
save_imatrix: stored collected data after 80 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[80]8.3615,[81]8.3437,[82]8.3309,[83]8.2756,[84]8.2916,[85]8.2987,[86]8.2900,[87]8.3182,[88]8.3145,[89]8.3015,
save_imatrix: stored collected data after 90 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[90]8.2822,[91]8.2930,[92]8.2448,[93]8.2390,[94]8.2104,[95]8.1747,[96]8.1994,[97]8.1919,[98]8.2019,[99]8.1808,
save_imatrix: stored collected data after 100 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[100]8.1697,[101]8.1935,[102]8.1551,[103]8.1190,[104]8.1010,[105]8.1276,[106]8.1249,[107]8.1380,[108]8.1674,[109]8.0909,
save_imatrix: stored collected data after 110 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[110]8.0305,[111]7.9669,[112]7.9005,[113]7.8343,[114]7.7723,[115]7.7137,[116]7.6576,[117]7.6158,[118]7.6329,[119]7.6453,
save_imatrix: stored collected data after 120 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[120]7.6954,[121]7.7506,[122]7.8016,[123]7.8576,[124]7.9541,[125]8.0482,[126]8.0601,[127]8.0794,[128]8.0077,[129]8.0114,
save_imatrix: stored collected data after 130 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[130]7.9939,[131]7.9857,[132]7.9606,[133]7.9555,[134]7.9690,[135]7.9940,[136]7.9830,[137]7.9785,[138]7.9913,[139]8.0043,
save_imatrix: stored collected data after 140 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[140]8.0231,[141]8.0263,[142]8.0282,[143]8.0130,[144]7.9915,[145]8.0111,[146]8.0400,[147]8.0742,[148]8.1063,[149]8.1451,
save_imatrix: stored collected data after 150 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat
[150]8.1810,[151]8.2203,
save_imatrix: stored collected data after 151 chunks in llm-compiler-7b-IMat-GGUF/imatrix.dat

llama_print_timings:        load time =    1857.95 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 =   81192.92 ms / 77312 tokens (    1.05 ms per token,   952.20 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 =   82973.02 ms / 77313 tokens

Final estimate: PPL = 8.2203 +/- 0.10580