Text Generation
GGUF
PyTorch
English
instruct
finance
stock market
candlesticks
FinGPT
option trading
future stock prediction
trends prediction
Enterprise LLM
Enterprise
Enterprise ready
Banks
Wealth Management
quantized
GGUF
quantization
imat
imatrix
static
32bit
16bit
8bit
6bit
5bit
4bit
3bit
2bit
1bit
conversational
File size: 11,206 Bytes
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llama_model_loader: loaded meta data with 32 key-value pairs and 723 tensors from Palmyra-Fin-70B-32K-IMat-GGUF/Palmyra-Fin-70B-32K.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.type str = model
llama_model_loader: - kv 2: general.name str = Palmyra Fin 70B 32K
llama_model_loader: - kv 3: general.organization str = Writer
llama_model_loader: - kv 4: general.finetune str = 32k
llama_model_loader: - kv 5: general.basename str = Palmyra-Fin
llama_model_loader: - kv 6: general.size_label str = 70B
llama_model_loader: - kv 7: general.license str = other
llama_model_loader: - kv 8: general.license.name str = writer-open-model-license
llama_model_loader: - kv 9: general.license.link str = https://writer.com/legal/open-model-l...
llama_model_loader: - kv 10: general.tags arr[str,14] = ["instruct", "pytorch", "finance", "s...
llama_model_loader: - kv 11: general.languages arr[str,1] = ["en"]
llama_model_loader: - kv 12: llama.block_count u32 = 80
llama_model_loader: - kv 13: llama.context_length u32 = 32768
llama_model_loader: - kv 14: llama.embedding_length u32 = 8192
llama_model_loader: - kv 15: llama.feed_forward_length u32 = 28672
llama_model_loader: - kv 16: llama.attention.head_count u32 = 64
llama_model_loader: - kv 17: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 18: llama.rope.freq_base f32 = 6315088.000000
llama_model_loader: - kv 19: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 20: general.file_type u32 = 7
llama_model_loader: - kv 21: llama.vocab_size u32 = 128256
llama_model_loader: - kv 22: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 23: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 24: tokenizer.ggml.pre str = smaug-bpe
llama_model_loader: - kv 25: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 27: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 28: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 29: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 30: tokenizer.chat_template str = {% set loop_messages = messages %}{% ...
llama_model_loader: - kv 31: general.quantization_version u32 = 2
llama_model_loader: - type f32: 161 tensors
llama_model_loader: - type q8_0: 562 tensors
llm_load_vocab: special tokens cache size = 256
llm_load_vocab: token to piece cache size = 0.8000 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: vocab_only = 0
llm_load_print_meta: n_ctx_train = 32768
llm_load_print_meta: n_embd = 8192
llm_load_print_meta: n_layer = 80
llm_load_print_meta: n_head = 64
llm_load_print_meta: n_head_kv = 8
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 = 8
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 = 28672
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 = 6315088.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn = 32768
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 = 70B
llm_load_print_meta: model ftype = Q8_0
llm_load_print_meta: model params = 70.55 B
llm_load_print_meta: model size = 69.82 GiB (8.50 BPW)
llm_load_print_meta: general.name = Palmyra Fin 70B 32K
llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>'
llm_load_print_meta: EOS token = 128009 '<|eot_id|>'
llm_load_print_meta: LF token = 128 'Ä'
llm_load_print_meta: EOT token = 128009 '<|eot_id|>'
llm_load_print_meta: max token length = 256
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 = 0.68 MiB
llm_load_tensors: offloading 25 repeating layers to GPU
llm_load_tensors: offloaded 25/81 layers to GPU
llm_load_tensors: CPU buffer size = 71494.28 MiB
llm_load_tensors: CUDA0 buffer size = 21676.56 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 = 6315088.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: CUDA_Host KV buffer size = 110.00 MiB
llama_kv_cache_init: CUDA0 KV buffer size = 50.00 MiB
llama_new_context_with_model: KV self size = 160.00 MiB, K (f16): 80.00 MiB, V (f16): 80.00 MiB
llama_new_context_with_model: CUDA_Host output buffer size = 0.49 MiB
llama_new_context_with_model: CUDA0 compute buffer size = 1331.12 MiB
llama_new_context_with_model: CUDA_Host compute buffer size = 17.01 MiB
llama_new_context_with_model: graph nodes = 2566
llama_new_context_with_model: graph splits = 609
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 126.907 ms
compute_imatrix: computing over 125 chunks with batch_size 512
compute_imatrix: 6.04 seconds per pass - ETA 12.58 minutes
[1]6.1440,[2]4.7452,[3]4.1216,[4]4.9314,[5]5.0081,[6]4.2135,[7]4.2735,[8]4.6681,[9]4.8739,
save_imatrix: stored collected data after 10 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[10]4.5858,[11]5.0261,[12]5.4656,[13]5.9165,[14]6.2804,[15]6.4814,[16]6.7611,[17]6.9371,[18]6.6649,[19]6.3427,
save_imatrix: stored collected data after 20 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[20]6.3391,[21]6.4281,[22]6.4250,[23]6.6474,[24]6.6518,[25]6.9319,[26]6.9256,[27]6.5617,[28]6.2843,[29]6.2872,
save_imatrix: stored collected data after 30 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[30]6.2545,[31]5.9800,[32]5.7160,[33]5.6005,[34]5.5069,[35]5.5871,[36]5.6482,[37]5.6162,[38]5.6794,[39]5.8489,
save_imatrix: stored collected data after 40 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[40]5.9275,[41]5.7433,[42]5.5645,[43]5.4150,[44]5.2665,[45]5.2281,[46]5.2048,[47]5.3152,[48]5.4025,[49]5.5079,
save_imatrix: stored collected data after 50 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[50]5.4590,[51]5.5551,[52]5.6457,[53]5.7308,[54]5.7917,[55]5.8764,[56]5.9336,[57]6.0021,[58]6.0446,[59]6.0770,
save_imatrix: stored collected data after 60 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[60]6.0581,[61]6.0574,[62]6.1048,[63]6.1625,[64]6.1075,[65]6.0976,[66]6.1092,[67]6.0971,[68]6.1110,[69]6.1082,
save_imatrix: stored collected data after 70 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[70]6.1211,[71]6.1250,[72]6.1348,[73]6.1226,[74]6.0961,[75]6.0962,[76]6.1081,[77]6.0929,[78]6.0968,[79]6.1313,
save_imatrix: stored collected data after 80 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[80]6.1531,[81]6.1465,[82]6.1606,[83]6.1917,[84]6.1254,[85]6.1244,[86]6.1312,[87]6.1491,[88]6.1875,[89]6.2506,
save_imatrix: stored collected data after 90 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[90]6.2899,[91]6.3202,[92]6.3413,[93]6.3615,[94]6.3904,[95]6.4258,[96]6.3927,[97]6.4068,[98]6.4536,[99]6.5224,
save_imatrix: stored collected data after 100 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[100]6.5836,[101]6.6276,[102]6.7285,[103]6.7596,[104]6.7928,[105]6.7456,[106]6.7562,[107]6.7182,[108]6.6500,[109]6.5811,
save_imatrix: stored collected data after 110 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[110]6.6171,[111]6.6546,[112]6.6663,[113]6.6677,[114]6.6948,[115]6.7273,[116]6.7414,[117]6.7599,[118]6.7975,[119]6.7594,
save_imatrix: stored collected data after 120 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
[120]6.6840,[121]6.6151,[122]6.5444,[123]6.4784,[124]6.4269,[125]6.3698,
save_imatrix: stored collected data after 125 chunks in Palmyra-Fin-70B-32K-IMat-GGUF/imatrix.dat
llama_print_timings: load time = 32479.28 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 = 707989.47 ms / 64000 tokens ( 11.06 ms per token, 90.40 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 = 735504.21 ms / 64001 tokens
Final estimate: PPL = 6.3698 +/- 0.08949
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