Log start main: build = 3070 (3413ae21) main: built with Clang 12.0.0 for x64 main: seed = 1 llama_model_loader: loaded meta data with 22 key-value pairs and 291 tensors from d:\code\test_llm\models\Meta-Llama-3-8B-Instruct_64K_Q8_0.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 = content llama_model_loader: - kv 2: llama.vocab_size u32 = 128256 llama_model_loader: - kv 3: llama.context_length u32 = 65536 llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 llama_model_loader: - kv 5: llama.block_count u32 = 32 llama_model_loader: - kv 6: llama.feed_forward_length u32 = 14336 llama_model_loader: - kv 7: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 8: llama.attention.head_count u32 = 32 llama_model_loader: - kv 9: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 10: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 11: llama.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 12: general.file_type u32 = 7 llama_model_loader: - kv 13: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 14: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 15: tokenizer.ggml.scores arr[f32,128256] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 16: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 17: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 128000 llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 128001 llama_model_loader: - kv 20: tokenizer.chat_template str = {% set loop_messages = messages %}{% ... llama_model_loader: - kv 21: general.quantization_version u32 = 2 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q8_0: 226 tensors validate_override: Using metadata override ( str) 'tokenizer.ggml.pre' = llama3 llm_load_vocab: special tokens cache size = 256 llm_load_vocab: token to piece cache size = 1.5928 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 = 128256 llm_load_print_meta: n_merges = 280147 llm_load_print_meta: n_ctx_train = 65536 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 = 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 = 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 = linear llm_load_print_meta: freq_base_train = 1000000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_yarn_orig_ctx = 65536 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 = 8B llm_load_print_meta: model ftype = Q8_0 llm_load_print_meta: model params = 8.03 B llm_load_print_meta: model size = 7.95 GiB (8.50 BPW) llm_load_print_meta: general.name = content llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>' llm_load_print_meta: EOS token = 128001 '<|end_of_text|>' llm_load_print_meta: LF token = 128 'Ä' llm_load_print_meta: EOT token = 128009 '<|eot_id|>' 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 2080 Ti, compute capability 7.5, VMM: yes llm_load_tensors: ggml ctx size = 0.30 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 = 532.31 MiB llm_load_tensors: CUDA0 buffer size = 7605.33 MiB ......................................................................................... llama_new_context_with_model: n_ctx = 65536 llama_new_context_with_model: n_batch = 2048 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 1 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 = 8192.00 MiB llama_new_context_with_model: KV self size = 8192.00 MiB, K (f16): 4096.00 MiB, V (f16): 4096.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 0.49 MiB ggml_gallocr_reserve_n: reallocating CUDA0 buffer from size 0.00 MiB to 258.50 MiB ggml_gallocr_reserve_n: reallocating CUDA_Host buffer from size 0.00 MiB to 136.01 MiB llama_new_context_with_model: CUDA0 compute buffer size = 258.50 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 136.01 MiB llama_new_context_with_model: graph nodes = 903 llama_new_context_with_model: graph splits = 2 ggml_backend_cuda_graph_compute enter ggml_backend_cuda_graph_compute:2554 cuda_graph_update_required=true (instance is null) ggml_backend_cuda_graph_compute:2559 cuda_graph_update_required=true (different count of nodes) ggml_backend_cuda_graph_compute: disabling CUDA graphs due to batch size > 1 [ffn_inp-0] [4096 2 1 1] ggml_backend_cuda_graph_compute exit system_info: n_threads = 1 / 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 | sampling: repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000 top_k = 40, tfs_z = 1.000, top_p = 0.950, min_p = 0.050, typical_p = 1.000, temp = 0.800 mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000 sampling order: CFG -> Penalties -> top_k -> tfs_z -> typical_p -> top_p -> min_p -> temperature generate: n_ctx = 65536, n_batch = 2048, n_predict = -1, n_keep = 0 ggml_backend_cuda_graph_compute enter ggml_backend_cuda_graph_compute:2554 cuda_graph_update_required=true (instance is null) ggml_backend_cuda_graph_compute exit In ggml_backend_cuda_graph_compute enter ggml_backend_cuda_graph_compute exit today ggml_backend_cuda_graph_compute enter ggml_backend_cuda_graph_compute exit 's ggml_backend_cuda_graph_compute enter ggml_backend_cuda_graph_compute exit society ggml_backend_cuda_graph_compute enter ggml_backend_cuda_graph_compute exit , ggml_backend_cuda_graph_compute enter ggml_backend_cuda_graph_compute exit social ggml_backend_cuda_graph_compute enter 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