-
Notifications
You must be signed in to change notification settings - Fork 12.4k
Closed
Labels
bug-unconfirmedcritical severityUsed to report critical severity bugs in llama.cpp (e.g. Crashing, Corrupted, Dataloss)Used to report critical severity bugs in llama.cpp (e.g. Crashing, Corrupted, Dataloss)
Description
What happened?
I am trying to use a quantized (q2_k) version of DeepSeek-Coder-V2-Instruct and it fails to load model completly - the process was killed every time I tried to run it after some time
Name and Version
./llama-cli --version
version: 3253 (ab36791)
built with Apple clang version 15.0.0 (clang-1500.3.9.4) for arm64-apple-darwin23.5.0
What operating system are you seeing the problem on?
Mac
Relevant log output
./llama-cli -m ./models/DeepSeek-Coder-V2-Instruct_q2_K.gguf --color -i --multiline-input --log-enable -p "just say hallo"
Log start
main: build = 3253 (ab367911)
main: built with Apple clang version 15.0.0 (clang-1500.3.9.4) for arm64-apple-darwin23.5.0
main: seed = 1719507332
llama_model_loader: loaded meta data with 39 key-value pairs and 959 tensors from ./models/DeepSeek-Coder-V2-Instruct_q2_K.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 = deepseek2
llama_model_loader: - kv 1: general.name str = DeepSeek-Coder-V2-Instruct
llama_model_loader: - kv 2: deepseek2.block_count u32 = 60
llama_model_loader: - kv 3: deepseek2.context_length u32 = 163840
llama_model_loader: - kv 4: deepseek2.embedding_length u32 = 5120
llama_model_loader: - kv 5: deepseek2.feed_forward_length u32 = 12288
llama_model_loader: - kv 6: deepseek2.attention.head_count u32 = 128
llama_model_loader: - kv 7: deepseek2.attention.head_count_kv u32 = 128
llama_model_loader: - kv 8: deepseek2.rope.freq_base f32 = 10000,000000
llama_model_loader: - kv 9: deepseek2.attention.layer_norm_rms_epsilon f32 = 0,000001
llama_model_loader: - kv 10: deepseek2.expert_used_count u32 = 6
llama_model_loader: - kv 11: general.file_type u32 = 10
llama_model_loader: - kv 12: deepseek2.leading_dense_block_count u32 = 1
llama_model_loader: - kv 13: deepseek2.vocab_size u32 = 102400
llama_model_loader: - kv 14: deepseek2.attention.q_lora_rank u32 = 1536
llama_model_loader: - kv 15: deepseek2.attention.kv_lora_rank u32 = 512
llama_model_loader: - kv 16: deepseek2.attention.key_length u32 = 192
llama_model_loader: - kv 17: deepseek2.attention.value_length u32 = 128
llama_model_loader: - kv 18: deepseek2.expert_feed_forward_length u32 = 1536
llama_model_loader: - kv 19: deepseek2.expert_count u32 = 160
llama_model_loader: - kv 20: deepseek2.expert_shared_count u32 = 2
llama_model_loader: - kv 21: deepseek2.expert_weights_scale f32 = 16,000000
llama_model_loader: - kv 22: deepseek2.rope.dimension_count u32 = 64
llama_model_loader: - kv 23: deepseek2.rope.scaling.type str = yarn
llama_model_loader: - kv 24: deepseek2.rope.scaling.factor f32 = 40,000000
llama_model_loader: - kv 25: deepseek2.rope.scaling.original_context_length u32 = 4096
llama_model_loader: - kv 26: deepseek2.rope.scaling.yarn_log_multiplier f32 = 0,100000
llama_model_loader: - kv 27: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 28: tokenizer.ggml.pre str = deepseek-llm
llama_model_loader: - kv 29: tokenizer.ggml.tokens arr[str,102400] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 30: tokenizer.ggml.token_type arr[i32,102400] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 31: tokenizer.ggml.merges arr[str,99757] = ["Ġ Ġ", "Ġ t", "Ġ a", "i n", "h e...
llama_model_loader: - kv 32: tokenizer.ggml.bos_token_id u32 = 100000
llama_model_loader: - kv 33: tokenizer.ggml.eos_token_id u32 = 100001
llama_model_loader: - kv 34: tokenizer.ggml.padding_token_id u32 = 100001
llama_model_loader: - kv 35: tokenizer.ggml.add_bos_token bool = true
llama_model_loader: - kv 36: tokenizer.ggml.add_eos_token bool = false
llama_model_loader: - kv 37: tokenizer.chat_template str = {% if not add_generation_prompt is de...
llama_model_loader: - kv 38: general.quantization_version u32 = 2
llama_model_loader: - type f32: 300 tensors
llama_model_loader: - type q2_K: 479 tensors
llama_model_loader: - type q3_K: 179 tensors
llama_model_loader: - type q6_K: 1 tensors
llm_load_vocab: special tokens cache size = 2400
llm_load_vocab: token to piece cache size = 0,6661 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = deepseek2
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 102400
llm_load_print_meta: n_merges = 99757
llm_load_print_meta: n_ctx_train = 163840
llm_load_print_meta: n_embd = 5120
llm_load_print_meta: n_head = 128
llm_load_print_meta: n_head_kv = 128
llm_load_print_meta: n_layer = 60
llm_load_print_meta: n_rot = 64
llm_load_print_meta: n_embd_head_k = 192
llm_load_print_meta: n_embd_head_v = 128
llm_load_print_meta: n_gqa = 1
llm_load_print_meta: n_embd_k_gqa = 24576
llm_load_print_meta: n_embd_v_gqa = 16384
llm_load_print_meta: f_norm_eps = 0,0e+00
llm_load_print_meta: f_norm_rms_eps = 1,0e-06
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 = 12288
llm_load_print_meta: n_expert = 160
llm_load_print_meta: n_expert_used = 6
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 = yarn
llm_load_print_meta: freq_base_train = 10000,0
llm_load_print_meta: freq_scale_train = 0,025
llm_load_print_meta: n_ctx_orig_yarn = 4096
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 = 236B
llm_load_print_meta: model ftype = Q2_K - Medium
llm_load_print_meta: model params = 235,74 B
llm_load_print_meta: model size = 80,04 GiB (2,92 BPW)
llm_load_print_meta: general.name = DeepSeek-Coder-V2-Instruct
llm_load_print_meta: BOS token = 100000 '<|begin▁of▁sentence|>'
llm_load_print_meta: EOS token = 100001 '<|end▁of▁sentence|>'
llm_load_print_meta: PAD token = 100001 '<|end▁of▁sentence|>'
llm_load_print_meta: LF token = 126 'Ä'
llm_load_print_meta: max token length = 256
llm_load_print_meta: n_layer_dense_lead = 1
llm_load_print_meta: n_lora_q = 1536
llm_load_print_meta: n_lora_kv = 512
llm_load_print_meta: n_ff_exp = 1536
llm_load_print_meta: n_expert_shared = 2
llm_load_print_meta: expert_weights_scale = 16,0
llm_load_print_meta: rope_yarn_log_mul = 0,1000
llm_load_tensors: ggml ctx size = 0,80 MiB
ggml_backend_metal_log_allocated_size: allocated buffer, size = 73728,00 MiB, (73728,08 / 98304,00)
ggml_backend_metal_log_allocated_size: allocated buffer, size = 8748,94 MiB, (82477,02 / 98304,00)
llm_load_tensors: offloading 60 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 61/61 layers to GPU
llm_load_tensors: Metal buffer size = 81961,29 MiB
llm_load_tensors: CPU buffer size = 164,06 MiB
....................................................................................................
llama_new_context_with_model: n_ctx = 163840
llama_new_context_with_model: n_batch = 2048
llama_new_context_with_model: n_ubatch = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base = 10000,0
llama_new_context_with_model: freq_scale = 0,025
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 = 103079,22 MB
zsh: killed ./llama-cli -m ./models/DeepSeek-Coder-V2-Instruct_q2_K.gguf --color -i -p
Metadata
Metadata
Assignees
Labels
bug-unconfirmedcritical severityUsed to report critical severity bugs in llama.cpp (e.g. Crashing, Corrupted, Dataloss)Used to report critical severity bugs in llama.cpp (e.g. Crashing, Corrupted, Dataloss)