salamandra-2b-instruct / perplexity_Q8_0.txt
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build: 3906 (7eee341b) with Apple clang version 15.0.0 (clang-1500.3.9.4) for arm64-apple-darwin23.6.0
llama_model_loader: loaded meta data with 35 key-value pairs and 219 tensors from salamandra-2b-instruct_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.type str = model
llama_model_loader: - kv 2: general.size_label str = 2.3B
llama_model_loader: - kv 3: general.license str = apache-2.0
llama_model_loader: - kv 4: general.tags arr[str,1] = ["text-generation"]
llama_model_loader: - kv 5: general.languages arr[str,36] = ["bg", "ca", "code", "cs", "cy", "da"...
llama_model_loader: - kv 6: llama.block_count u32 = 24
llama_model_loader: - kv 7: llama.context_length u32 = 8192
llama_model_loader: - kv 8: llama.embedding_length u32 = 2048
llama_model_loader: - kv 9: llama.feed_forward_length u32 = 5440
llama_model_loader: - kv 10: llama.attention.head_count u32 = 16
llama_model_loader: - kv 11: llama.attention.head_count_kv u32 = 16
llama_model_loader: - kv 12: llama.rope.freq_base f32 = 10000.000000
llama_model_loader: - kv 13: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 14: general.file_type u32 = 7
llama_model_loader: - kv 15: llama.vocab_size u32 = 256000
llama_model_loader: - kv 16: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 17: tokenizer.ggml.add_space_prefix bool = true
llama_model_loader: - kv 18: tokenizer.ggml.model str = llama
llama_model_loader: - kv 19: tokenizer.ggml.pre str = default
llama_model_loader: - kv 20: tokenizer.ggml.tokens arr[str,256000] = ["<unk>", "<s>", "</s>", "<pad>", "<|...
llama_model_loader: - kv 21: tokenizer.ggml.scores arr[f32,256000] = [-1000.000000, -1000.000000, -1000.00...
llama_model_loader: - kv 22: tokenizer.ggml.token_type arr[i32,256000] = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
llama_model_loader: - kv 23: tokenizer.ggml.bos_token_id u32 = 1
llama_model_loader: - kv 24: tokenizer.ggml.eos_token_id u32 = 2
llama_model_loader: - kv 25: tokenizer.ggml.unknown_token_id u32 = 0
llama_model_loader: - kv 26: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - kv 27: tokenizer.ggml.add_bos_token bool = true
llama_model_loader: - kv 28: tokenizer.ggml.add_eos_token bool = false
llama_model_loader: - kv 29: tokenizer.chat_template str = {%- if not date_string is defined %}{...
llama_model_loader: - kv 30: general.quantization_version u32 = 2
llama_model_loader: - kv 31: quantize.imatrix.file str = imatrix/oscar/imatrix.dat
llama_model_loader: - kv 32: quantize.imatrix.dataset str = ./imatrix/oscar/imatrix-dataset.txt
llama_model_loader: - kv 33: quantize.imatrix.entries_count i32 = 168
llama_model_loader: - kv 34: quantize.imatrix.chunks_count i32 = 44176
llama_model_loader: - type f32: 49 tensors
llama_model_loader: - type q8_0: 169 tensors
llama_model_loader: - type bf16: 1 tensors
llm_load_vocab: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
llm_load_vocab: special tokens cache size = 104
llm_load_vocab: token to piece cache size = 1.8842 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 = 256000
llm_load_print_meta: n_merges = 0
llm_load_print_meta: vocab_only = 0
llm_load_print_meta: n_ctx_train = 8192
llm_load_print_meta: n_embd = 2048
llm_load_print_meta: n_layer = 24
llm_load_print_meta: n_head = 16
llm_load_print_meta: n_head_kv = 16
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_swa = 0
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 = 2048
llm_load_print_meta: n_embd_v_gqa = 2048
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 = 5440
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 = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn = 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: ssm_dt_b_c_rms = 0
llm_load_print_meta: model type = ?B
llm_load_print_meta: model ftype = Q8_0
llm_load_print_meta: model params = 2.25 B
llm_load_print_meta: model size = 2.69 GiB (10.25 BPW)
llm_load_print_meta: general.name = n/a
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: PAD token = 0 '<unk>'
llm_load_print_meta: LF token = 145 '<0x0A>'
llm_load_print_meta: EOT token = 5 '<|im_end|>'
llm_load_print_meta: EOG token = 2 '</s>'
llm_load_print_meta: EOG token = 5 '<|im_end|>'
llm_load_print_meta: max token length = 72
llm_load_tensors: ggml ctx size = 0.20 MiB
llm_load_tensors: offloading 24 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 25/25 layers to GPU
llm_load_tensors: Metal buffer size = 2752.45 MiB
llm_load_tensors: CPU buffer size = 531.25 MiB
..............................................
llama_new_context_with_model: n_ctx = 8192
llama_new_context_with_model: n_batch = 512
llama_new_context_with_model: n_ubatch = 128
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
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M3 Max
ggml_metal_init: picking default device: Apple M3 Max
ggml_metal_init: using embedded metal library
ggml_metal_init: GPU name: Apple M3 Max
ggml_metal_init: GPU family: MTLGPUFamilyApple9 (1009)
ggml_metal_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_init: GPU family: MTLGPUFamilyMetal3 (5001)
ggml_metal_init: simdgroup reduction support = true
ggml_metal_init: simdgroup matrix mul. support = true
ggml_metal_init: hasUnifiedMemory = true
ggml_metal_init: recommendedMaxWorkingSetSize = 42949.67 MB
llama_kv_cache_init: Metal KV buffer size = 1536.00 MiB
llama_new_context_with_model: KV self size = 1536.00 MiB, K (f16): 768.00 MiB, V (f16): 768.00 MiB
llama_new_context_with_model: CPU output buffer size = 0.98 MiB
llama_new_context_with_model: Metal compute buffer size = 72.00 MiB
llama_new_context_with_model: CPU compute buffer size = 125.00 MiB
llama_new_context_with_model: graph nodes = 774
llama_new_context_with_model: graph splits = 3
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
system_info: n_threads = 15 (n_threads_batch = 15) / 16 | AVX = 0 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 1 | SVE = 0 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | RISCV_VECT = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 1 | LLAMAFILE = 1 |
perplexity: tokenizing the input ..
perplexity: tokenization took 2890.81 ms
perplexity: calculating perplexity over 134 chunks, n_ctx=8192, batch_size=512, n_seq=1
perplexity: 9.66 seconds per pass - ETA 21.57 minutes
[1]17.0900,[2]17.2426,[3]15.6960,[4]15.5004,[5]14.8627,[6]14.4270,[7]15.3004,[8]14.7900,[9]14.5098,[10]13.8086,[11]14.4216,[12]14.4788,[13]15.5017,[14]15.7599,[15]15.7465,[16]16.2741,[17]16.5646,[18]16.4675,[19]16.5092,[20]16.8109,[21]16.8498,[22]14.8777,[23]15.0527,[24]14.6855,[25]14.1820,[26]13.7497,[27]13.5624,[28]13.3915,[29]13.3436,[30]13.1437,[31]13.3746,[32]13.4818,[33]13.9475,[34]14.2460,[35]14.5429,[36]14.3139,[37]14.3042,[38]14.3798,[39]14.2324,[40]14.2660,[41]14.2413,[42]14.0575,[43]14.0072,[44]14.1687,[45]14.3701,[46]14.2268,[47]14.4577,[48]14.5686,[49]14.8366,[50]15.1069,[51]15.1403,[52]15.3456,[53]15.6561,[54]15.9664,[55]16.0721,[56]15.9099,[57]15.8156,[58]15.5525,[59]15.4494,[60]15.2612,[61]15.3116,[62]15.4426,[63]15.6231,[64]15.6839,[65]15.7118,[66]15.8945,[67]15.8694,[68]15.7612,[69]15.6235,[70]15.5194,[71]15.5137,[72]15.4592,[73]15.4688,[74]15.4122,[75]15.3869,[76]15.3275,[77]15.3844,[78]15.3841,[79]15.3929,[80]15.4288,[81]15.1483,[82]15.1268,[83]14.9998,[84]15.0316,[85]15.0785,[86]15.2672,[87]15.2901,[88]15.4407,[89]15.4927,[90]15.6146,[91]15.6685,[92]15.5091,[93]15.5730,[94]15.5610,[95]15.6941,[96]15.8808,[97]15.9547,[98]16.0485,[99]16.1837,[100]16.2244,[101]16.2508,[102]16.2129,[103]16.1850,[104]16.1688,[105]16.1554,[106]16.0302,[107]15.9058,[108]15.9652,[109]15.9820,[110]15.8958,[111]15.8602,[112]15.7149,[113]15.5783,[114]15.5728,[115]15.5477,[116]15.5567,[117]15.4532,[118]15.3271,[119]15.3203,[120]15.3782,[121]15.3928,[122]15.4152,[123]15.4498,[124]15.4654,[125]15.4595,[126]15.4843,[127]15.5078,[128]15.5850,[129]15.5754,[130]15.5533,[131]15.6085,[132]15.5844,[133]15.5300,[134]15.3831,
Final estimate: PPL = 15.3831 +/- 0.06266
llama_perf_context_print: load time = 1576.71 ms
llama_perf_context_print: prompt eval time = 1364068.65 ms / 1097728 tokens ( 1.24 ms per token, 804.75 tokens per second)
llama_perf_context_print: eval time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second)
llama_perf_context_print: total time = 1400622.10 ms / 1097729 tokens
ggml_metal_free: deallocating