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Qwen2.5-Coder-7B-Instruct-IMat-GGUF

Text Generation
GGUF
English
code
codeqwen
chat
qwen
qwen-coder
quantized
GGUF
quantization
imat
imatrix
static
16bit
8bit
6bit
5bit
4bit
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imatrix.log ADDED
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+ build: 3787 (6026da52) with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
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+ llama_model_loader: loaded meta data with 34 key-value pairs and 339 tensors from Qwen2.5-Coder-7B-Instruct-IMat-GGUF/Qwen2.5-Coder-7B-Instruct.Q8_0.gguf.hardlink.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.type str = model
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+ llama_model_loader: - kv 2: general.name str = Qwen2.5 Coder 7B Instruct
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+ llama_model_loader: - kv 3: general.finetune str = Instruct
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+ llama_model_loader: - kv 4: general.basename str = Qwen2.5-Coder
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+ llama_model_loader: - kv 5: general.size_label str = 7B
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+ llama_model_loader: - kv 6: general.license str = apache-2.0
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+ llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/Qwen/Qwen2.5-C...
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+ llama_model_loader: - kv 8: general.base_model.count u32 = 1
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+ llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 Coder 7B
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+ llama_model_loader: - kv 10: general.base_model.0.organization str = Qwen
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+ llama_model_loader: - kv 11: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen2.5-C...
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+ llama_model_loader: - kv 12: general.tags arr[str,6] = ["code", "codeqwen", "chat", "qwen", ...
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+ llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"]
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+ llama_model_loader: - kv 14: qwen2.block_count u32 = 28
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+ llama_model_loader: - kv 15: qwen2.context_length u32 = 32768
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+ llama_model_loader: - kv 16: qwen2.embedding_length u32 = 3584
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+ llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 18944
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+ llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 28
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+ llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 4
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+ llama_model_loader: - kv 20: qwen2.rope.freq_base f32 = 1000000.000000
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+ llama_model_loader: - kv 21: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001
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+ llama_model_loader: - kv 22: general.file_type u32 = 7
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+ llama_model_loader: - kv 23: tokenizer.ggml.model str = gpt2
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+ llama_model_loader: - kv 24: tokenizer.ggml.pre str = qwen2
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+ llama_model_loader: - kv 25: tokenizer.ggml.tokens arr[str,152064] = ["!", "\"", "#", "$", "%", "&", "'", ...
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+ llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
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+ llama_model_loader: - kv 27: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
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+ llama_model_loader: - kv 28: tokenizer.ggml.eos_token_id u32 = 151645
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+ llama_model_loader: - kv 29: tokenizer.ggml.padding_token_id u32 = 151643
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+ llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643
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+ llama_model_loader: - kv 31: tokenizer.ggml.add_bos_token bool = false
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+ llama_model_loader: - kv 32: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
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+ llama_model_loader: - kv 33: general.quantization_version u32 = 2
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+ llama_model_loader: - type f32: 141 tensors
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+ llama_model_loader: - type q8_0: 198 tensors
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+ llm_load_vocab: special tokens cache size = 22
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+ llm_load_vocab: token to piece cache size = 0.9310 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 = 152064
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+ llm_load_print_meta: n_merges = 151387
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+ llm_load_print_meta: vocab_only = 0
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+ llm_load_print_meta: n_ctx_train = 32768
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+ llm_load_print_meta: n_embd = 3584
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+ llm_load_print_meta: n_layer = 28
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+ llm_load_print_meta: n_head = 28
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+ llm_load_print_meta: n_head_kv = 4
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+ llm_load_print_meta: n_rot = 128
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+ llm_load_print_meta: n_swa = 0
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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 = 7
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+ llm_load_print_meta: n_embd_k_gqa = 512
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+ llm_load_print_meta: n_embd_v_gqa = 512
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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 = 18944
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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_ctx_orig_yarn = 32768
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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: ssm_dt_b_c_rms = 0
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+ llm_load_print_meta: model type = ?B
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+ llm_load_print_meta: model ftype = Q8_0
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+ llm_load_print_meta: model params = 7.62 B
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+ llm_load_print_meta: model size = 7.54 GiB (8.50 BPW)
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+ llm_load_print_meta: general.name = Qwen2.5 Coder 7B Instruct
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+ llm_load_print_meta: BOS token = 151643 '<|endoftext|>'
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+ llm_load_print_meta: EOS token = 151645 '<|im_end|>'
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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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+ llm_load_print_meta: max token length = 256
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+ ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
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+ ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
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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 = 0.30 MiB
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+ llm_load_tensors: offloading 28 repeating layers to GPU
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+ llm_load_tensors: offloading non-repeating layers to GPU
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+ llm_load_tensors: offloaded 29/29 layers to GPU
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+ llm_load_tensors: CPU buffer size = 552.23 MiB
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+ llm_load_tensors: CUDA0 buffer size = 7165.44 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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+ llama_kv_cache_init: CUDA0 KV buffer size = 28.00 MiB
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+ llama_new_context_with_model: KV self size = 28.00 MiB, K (f16): 14.00 MiB, V (f16): 14.00 MiB
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+ llama_new_context_with_model: CUDA_Host output buffer size = 0.58 MiB
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+ llama_new_context_with_model: CUDA0 compute buffer size = 304.00 MiB
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+ llama_new_context_with_model: CUDA_Host compute buffer size = 8.01 MiB
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+ llama_new_context_with_model: graph nodes = 986
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+ llama_new_context_with_model: graph splits = 2
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+
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+ system_info: n_threads = 25 (n_threads_batch = 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 | RISCV_VECT = 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 144.884 ms
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+ compute_imatrix: computing over 128 chunks with batch_size 512
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+ compute_imatrix: 0.69 seconds per pass - ETA 1.45 minutes
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+ [1]6.0084,[2]4.0626,[3]4.0763,[4]4.6739,[5]4.4992,[6]4.1794,[7]4.6612,[8]4.6825,[9]5.1452,[10]4.9525,[11]4.8026,[12]5.2632,[13]5.9347,[14]6.2123,[15]6.8152,[16]7.1605,[17]7.3811,[18]7.8707,[19]7.6353,[20]7.7660,[21]7.8885,[22]7.9039,[23]7.6916,[24]7.9418,[25]8.1131,[26]8.0023,[27]8.1630,[28]8.3365,[29]8.6709,[30]8.7003,[31]8.4068,[32]8.0191,[33]7.8185,[34]7.7005,[35]7.6005,[36]7.6719,[37]7.8548,[38]7.9550,[39]8.0013,[40]8.2275,[41]8.2863,[42]8.6029,[43]8.8723,[44]9.1375,[45]9.3272,[46]9.4485,[47]9.2844,[48]9.3362,[49]9.4397,[50]9.4900,[51]9.3574,[52]9.4395,[53]9.6470,[54]9.7485,[55]9.8657,[56]9.9389,[57]9.9881,[58]10.0312,[59]10.0292,[60]9.9706,[61]9.9334,[62]9.8877,[63]9.9299,[64]9.9847,[65]9.9124,[66]9.8971,[67]9.8920,[68]9.7819,[69]9.6992,[70]9.6702,[71]9.6032,[72]9.5626,[73]9.5611,[74]9.4581,[75]9.3616,[76]9.2824,[77]9.2574,[78]9.2367,[79]9.1978,[80]9.0967,[81]9.1231,[82]9.1089,[83]9.0391,[84]9.0708,[85]9.0815,[86]9.0088,[87]8.9793,[88]8.9727,[89]8.9870,[90]9.0012,[91]8.9826,[92]8.9083,[93]8.8303,[94]8.7458,[95]8.6693,[96]8.6052,[97]8.5277,[98]8.4588,[99]8.4252,[100]8.4379,[101]8.4679,[102]8.5896,[103]8.7091,[104]8.8020,[105]8.9496,[106]9.0476,[107]9.0833,[108]9.0487,[109]9.0566,[110]9.0177,[111]8.9646,[112]8.8785,[113]8.8573,[114]8.9144,[115]8.9344,[116]8.9597,[117]8.9810,[118]9.0244,[119]9.0241,[120]9.0217,[121]9.0412,[122]8.9863,[123]9.0292,[124]9.0783,[125]9.1227,[126]9.1894,[127]9.2485,[128]9.3054,
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+ Final estimate: PPL = 9.3054 +/- 0.14411
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+
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+ llama_perf_context_print: load time = 2452.34 ms
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+ llama_perf_context_print: prompt eval time = 68727.76 ms / 65536 tokens ( 1.05 ms per token, 953.56 tokens per second)
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+ llama_perf_context_print: eval time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second)
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+ llama_perf_context_print: total time = 71486.40 ms / 65537 tokens