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Delete imatrix.log
Browse files- imatrix.log +0 -114
imatrix.log
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main: build = 3051 (5921b8f0)
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main: built with cc (Ubuntu 13.2.0-23ubuntu4) 13.2.0 for x86_64-linux-gnu
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main: seed = 1717155952
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llama_model_loader: loaded meta data with 24 key-value pairs and 255 tensors from neo_7b-IMat-GGUF/neo_7b.gguf (version GGUF V3 (latest))
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llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
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llama_model_loader: - kv 0: general.architecture str = llama
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llama_model_loader: - kv 1: general.name str = neo_7b
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llama_model_loader: - kv 2: llama.block_count u32 = 28
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llama_model_loader: - kv 3: llama.context_length u32 = 8192
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llama_model_loader: - kv 4: llama.embedding_length u32 = 3072
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llama_model_loader: - kv 5: llama.feed_forward_length u32 = 24576
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llama_model_loader: - kv 6: llama.attention.head_count u32 = 16
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llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 16
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llama_model_loader: - kv 8: llama.rope.freq_base f32 = 10000.000000
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llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
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llama_model_loader: - kv 10: general.file_type u32 = 0
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llama_model_loader: - kv 11: llama.vocab_size u32 = 64256
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llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 192
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llama_model_loader: - kv 13: tokenizer.ggml.model str = llama
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llama_model_loader: - kv 14: tokenizer.ggml.pre str = default
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llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,64256] = ["<unk>", "<s>", "</s>", "<0x00>", "<...
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llama_model_loader: - kv 16: tokenizer.ggml.scores arr[f32,64256] = [0.000000, 0.000000, 0.000000, 0.0000...
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llama_model_loader: - kv 17: tokenizer.ggml.token_type arr[i32,64256] = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
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llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 1
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llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 2
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llama_model_loader: - kv 20: tokenizer.ggml.add_bos_token bool = false
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llama_model_loader: - kv 21: tokenizer.ggml.add_eos_token bool = false
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llama_model_loader: - kv 22: tokenizer.chat_template str = {% set system_message = 'You are a he...
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llama_model_loader: - kv 23: general.quantization_version u32 = 2
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llama_model_loader: - type f32: 255 tensors
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llm_load_vocab: special tokens cache size = 515
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llm_load_vocab: token to piece cache size = 0.7263 MB
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llm_load_print_meta: format = GGUF V3 (latest)
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llm_load_print_meta: arch = llama
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llm_load_print_meta: vocab type = SPM
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llm_load_print_meta: n_vocab = 64256
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llm_load_print_meta: n_merges = 0
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llm_load_print_meta: n_ctx_train = 8192
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llm_load_print_meta: n_embd = 3072
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llm_load_print_meta: n_head = 16
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llm_load_print_meta: n_head_kv = 16
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llm_load_print_meta: n_layer = 28
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llm_load_print_meta: n_rot = 192
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llm_load_print_meta: n_embd_head_k = 192
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llm_load_print_meta: n_embd_head_v = 192
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llm_load_print_meta: n_gqa = 1
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llm_load_print_meta: n_embd_k_gqa = 3072
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llm_load_print_meta: n_embd_v_gqa = 3072
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llm_load_print_meta: f_norm_eps = 0.0e+00
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llm_load_print_meta: f_norm_rms_eps = 1.0e-05
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llm_load_print_meta: f_clamp_kqv = 0.0e+00
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llm_load_print_meta: f_max_alibi_bias = 0.0e+00
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llm_load_print_meta: f_logit_scale = 0.0e+00
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llm_load_print_meta: n_ff = 24576
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llm_load_print_meta: n_expert = 0
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llm_load_print_meta: n_expert_used = 0
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llm_load_print_meta: causal attn = 1
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llm_load_print_meta: pooling type = 0
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llm_load_print_meta: rope type = 0
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llm_load_print_meta: rope scaling = linear
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llm_load_print_meta: freq_base_train = 10000.0
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llm_load_print_meta: freq_scale_train = 1
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llm_load_print_meta: n_yarn_orig_ctx = 8192
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llm_load_print_meta: rope_finetuned = unknown
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llm_load_print_meta: ssm_d_conv = 0
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llm_load_print_meta: ssm_d_inner = 0
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llm_load_print_meta: ssm_d_state = 0
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llm_load_print_meta: ssm_dt_rank = 0
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llm_load_print_meta: model type = ?B
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llm_load_print_meta: model ftype = all F32
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llm_load_print_meta: model params = 7.79 B
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llm_load_print_meta: model size = 29.03 GiB (32.00 BPW)
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llm_load_print_meta: general.name = neo_7b
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llm_load_print_meta: BOS token = 1 '<s>'
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llm_load_print_meta: EOS token = 2 '</s>'
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llm_load_print_meta: UNK token = 0 '<unk>'
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llm_load_print_meta: LF token = 13 '<0x0A>'
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ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
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ggml_cuda_init: CUDA_USE_TENSOR_CORES: yes
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ggml_cuda_init: found 1 CUDA devices:
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Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes
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llm_load_tensors: ggml ctx size = 0.26 MiB
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llm_load_tensors: offloading 24 repeating layers to GPU
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llm_load_tensors: offloaded 24/29 layers to GPU
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llm_load_tensors: CPU buffer size = 29730.67 MiB
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llm_load_tensors: CUDA0 buffer size = 24192.56 MiB
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.................................................................................................
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llama_new_context_with_model: n_ctx = 512
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llama_new_context_with_model: n_batch = 512
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llama_new_context_with_model: n_ubatch = 512
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llama_new_context_with_model: flash_attn = 0
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llama_new_context_with_model: freq_base = 10000.0
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llama_new_context_with_model: freq_scale = 1
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llama_kv_cache_init: CUDA_Host KV buffer size = 24.00 MiB
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llama_kv_cache_init: CUDA0 KV buffer size = 144.00 MiB
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llama_new_context_with_model: KV self size = 168.00 MiB, K (f16): 84.00 MiB, V (f16): 84.00 MiB
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llama_new_context_with_model: CUDA_Host output buffer size = 0.25 MiB
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llama_new_context_with_model: CUDA0 compute buffer size = 884.50 MiB
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llama_new_context_with_model: CUDA_Host compute buffer size = 13.01 MiB
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llama_new_context_with_model: graph nodes = 902
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llama_new_context_with_model: graph splits = 48
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system_info: n_threads = 25 / 32 | AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | 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 |
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compute_imatrix: tokenizing the input ..
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compute_imatrix: tokenization took 104.506 ms
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compute_imatrix: computing over 149 chunks with batch_size 512
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compute_imatrix: 7.05 seconds per pass - ETA 17.48 minutes
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[1]5.5510,[2]4.2655,[3]4.5181,[4]4.7129,[5]4.6112,[6]4.4538,[7]3.9156,[8]3.9898,[9]4.0393,
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save_imatrix: stored collected data after 10 chunks in neo_7b-IMat-GGUF/imatrix.dat
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[10]4.3880,[11]4.3659,[12]4.1373,[13]4.4218,[14]4.8427,[15]5.0896,[16]5.4727,[17]5.7076,[18]5.9118,[19]6.0551,
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save_imatrix: stored collected data after 20 chunks in neo_7b-IMat-GGUF/imatrix.dat
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[20]6.3265,[21]6.1195,[22]6.1174,[23]6.1416,[24]6.2290,[25]6.1717,[26]6.1541,[27]6.2767,[28]6.4483,[29]6.6253,
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save_imatrix: stored collected data after 30 chunks in neo_7b-IMat-GGUF/imatrix.dat
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[30]6.6419,[31]6.7306,[32]6.8220,[33]6.8508,[34]6.7559,
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