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main: build = 3086 (554c247c) |
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main: built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu |
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main: seed = 1717701152 |
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llama_model_loader: loaded meta data with 21 key-value pairs and 338 tensors from Qwen2-1.5B-IMat-GGUF/Qwen2-1.5B.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 = qwen2 |
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llama_model_loader: - kv 1: general.name str = Qwen2-1.5B |
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llama_model_loader: - kv 2: qwen2.block_count u32 = 28 |
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llama_model_loader: - kv 3: qwen2.context_length u32 = 131072 |
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llama_model_loader: - kv 4: qwen2.embedding_length u32 = 1536 |
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llama_model_loader: - kv 5: qwen2.feed_forward_length u32 = 8960 |
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llama_model_loader: - kv 6: qwen2.attention.head_count u32 = 12 |
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llama_model_loader: - kv 7: qwen2.attention.head_count_kv u32 = 2 |
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llama_model_loader: - kv 8: qwen2.rope.freq_base f32 = 1000000.000000 |
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llama_model_loader: - kv 9: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001 |
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llama_model_loader: - kv 10: general.file_type u32 = 0 |
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llama_model_loader: - kv 11: tokenizer.ggml.model str = gpt2 |
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llama_model_loader: - kv 12: tokenizer.ggml.pre str = qwen2 |
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llama_model_loader: - kv 13: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... |
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llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... |
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llama_model_loader: - kv 15: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... |
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llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 151643 |
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llama_model_loader: - kv 17: tokenizer.ggml.padding_token_id u32 = 151643 |
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llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 151643 |
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llama_model_loader: - kv 19: tokenizer.chat_template str = {% for message in messages %}{% if lo... |
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llama_model_loader: - kv 20: general.quantization_version u32 = 2 |
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llama_model_loader: - type f32: 338 tensors |
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llm_load_vocab: special tokens cache size = 293 |
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llm_load_vocab: token to piece cache size = 0.9338 MB |
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llm_load_print_meta: format = GGUF V3 (latest) |
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llm_load_print_meta: arch = qwen2 |
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llm_load_print_meta: vocab type = BPE |
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llm_load_print_meta: n_vocab = 151936 |
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llm_load_print_meta: n_merges = 151387 |
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llm_load_print_meta: n_ctx_train = 131072 |
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llm_load_print_meta: n_embd = 1536 |
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llm_load_print_meta: n_head = 12 |
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llm_load_print_meta: n_head_kv = 2 |
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llm_load_print_meta: n_layer = 28 |
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llm_load_print_meta: n_rot = 128 |
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llm_load_print_meta: n_embd_head_k = 128 |
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llm_load_print_meta: n_embd_head_v = 128 |
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llm_load_print_meta: n_gqa = 6 |
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llm_load_print_meta: n_embd_k_gqa = 256 |
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llm_load_print_meta: n_embd_v_gqa = 256 |
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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-06 |
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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 = 8960 |
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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 = 2 |
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llm_load_print_meta: rope scaling = linear |
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llm_load_print_meta: freq_base_train = 1000000.0 |
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llm_load_print_meta: freq_scale_train = 1 |
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llm_load_print_meta: n_yarn_orig_ctx = 131072 |
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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 = 1.54 B |
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llm_load_print_meta: model size = 5.75 GiB (32.00 BPW) |
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llm_load_print_meta: general.name = Qwen2-1.5B |
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llm_load_print_meta: BOS token = 151643 '<|endoftext|>' |
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llm_load_print_meta: EOS token = 151643 '<|endoftext|>' |
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llm_load_print_meta: PAD token = 151643 '<|endoftext|>' |
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llm_load_print_meta: LF token = 148848 'ÄĬ' |
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llm_load_print_meta: EOT token = 151645 '<|im_end|>' |
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ggml_cuda_init: failed to initialize CUDA: no CUDA-capable device is detected |
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llm_load_tensors: ggml ctx size = 0.16 MiB |
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llm_load_tensors: offloading 0 repeating layers to GPU |
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llm_load_tensors: offloaded 0/29 layers to GPU |
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llm_load_tensors: CPU buffer size = 5888.80 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 = 1000000.0 |
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llama_new_context_with_model: freq_scale = 1 |
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ggml_cuda_host_malloc: failed to allocate 14.00 MiB of pinned memory: no CUDA-capable device is detected |
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llama_kv_cache_init: CPU KV buffer size = 14.00 MiB |
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llama_new_context_with_model: KV self size = 14.00 MiB, K (f16): 7.00 MiB, V (f16): 7.00 MiB |
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ggml_cuda_host_malloc: failed to allocate 0.58 MiB of pinned memory: no CUDA-capable device is detected |
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llama_new_context_with_model: CPU output buffer size = 0.58 MiB |
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ggml_cuda_host_malloc: failed to allocate 299.75 MiB of pinned memory: no CUDA-capable device is detected |
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llama_new_context_with_model: CUDA_Host compute buffer size = 299.75 MiB |
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llama_new_context_with_model: graph nodes = 986 |
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llama_new_context_with_model: graph splits = 1 |
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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 | |
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compute_imatrix: tokenizing the input .. |
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compute_imatrix: tokenization took 132.724 ms |
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compute_imatrix: computing over 128 chunks with batch_size 512 |
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ggml_cuda_host_malloc: failed to allocate 296.75 MiB of pinned memory: no CUDA-capable device is detected |
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compute_imatrix: 1.39 seconds per pass - ETA 2.95 minutes |
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[1]6.8310,[2]5.0865,[3]4.9045,[4]5.7534,[5]5.5805,[6]5.0977,[7]5.6114,[8]5.8680,[9]6.4515, |
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save_imatrix: stored collected data after 10 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[10]6.1249,[11]5.9925,[12]6.4407,[13]7.0994,[14]7.3519,[15]7.9053,[16]8.2930,[17]8.3769,[18]8.8281,[19]8.5072, |
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save_imatrix: stored collected data after 20 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[20]8.6061,[21]8.6876,[22]8.6361,[23]8.5178,[24]8.7923,[25]8.9344,[26]8.8643,[27]9.1011,[28]9.3344,[29]9.6089, |
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save_imatrix: stored collected data after 30 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[30]9.4937,[31]9.1482,[32]8.7634,[33]8.5299,[34]8.3876,[35]8.2342,[36]8.2597,[37]8.3609,[38]8.4612,[39]8.4937, |
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save_imatrix: stored collected data after 40 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[40]8.6398,[41]8.6845,[42]9.0562,[43]9.4092,[44]9.7224,[45]9.9733,[46]10.1141,[47]9.9399,[48]9.9791,[49]10.0713, |
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save_imatrix: stored collected data after 50 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[50]10.1292,[51]10.0033,[52]10.0878,[53]10.2782,[54]10.3869,[55]10.4997,[56]10.5322,[57]10.5581,[58]10.5937,[59]10.5862, |
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save_imatrix: stored collected data after 60 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[60]10.5942,[61]10.5091,[62]10.4544,[63]10.5051,[64]10.5805,[65]10.5179,[66]10.5171,[67]10.5130,[68]10.4356,[69]10.3929, |
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save_imatrix: stored collected data after 70 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[70]10.3745,[71]10.3297,[72]10.3021,[73]10.3111,[74]10.2226,[75]10.1434,[76]10.0614,[77]10.0333,[78]10.0192,[79]9.9961, |
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save_imatrix: stored collected data after 80 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[80]9.9322,[81]9.9510,[82]9.9338,[83]9.8650,[84]9.9019,[85]9.9247,[86]9.8608,[87]9.8144,[88]9.7875,[89]9.8041, |
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save_imatrix: stored collected data after 90 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[90]9.8123,[91]9.7907,[92]9.6967,[93]9.6038,[94]9.5072,[95]9.4135,[96]9.3363,[97]9.2462,[98]9.1638,[99]9.1250, |
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save_imatrix: stored collected data after 100 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[100]9.1297,[101]9.1536,[102]9.2735,[103]9.3740,[104]9.4593,[105]9.6004,[106]9.6949,[107]9.7324,[108]9.6984,[109]9.6914, |
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save_imatrix: stored collected data after 110 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[110]9.6954,[111]9.6790,[112]9.6371,[113]9.6607,[114]9.7115,[115]9.7024,[116]9.7042,[117]9.7184,[118]9.7535,[119]9.7425, |
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save_imatrix: stored collected data after 120 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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[120]9.7342,[121]9.7356,[122]9.6908,[123]9.7388,[124]9.8151,[125]9.8718,[126]9.9517,[127]10.0170,[128]10.0816, |
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save_imatrix: stored collected data after 128 chunks in Qwen2-1.5B-IMat-GGUF/imatrix.dat |
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llama_print_timings: load time = 1724.51 ms |
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llama_print_timings: sample time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second) |
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llama_print_timings: prompt eval time = 200282.33 ms / 65536 tokens ( 3.06 ms per token, 327.22 tokens per second) |
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llama_print_timings: eval time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second) |
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llama_print_timings: total time = 201514.46 ms / 65537 tokens |
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Final estimate: PPL = 10.0816 +/- 0.14686 |
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