Misc. bug: [Mac M4]llama-server cannot run in release-4409 but can run in 4406 #11083
Description
Name and Version
llama-b4409-bin-macos-arm64.zip
llama-b4406-bin-macos-arm64.zip
Operating systems
Mac
Which llama.cpp modules do you know to be affected?
llama-server
Problem description & steps to reproduce
4409 run log:
/Users/liwenbo/Downloads/4409-llamacpp/bin/llama-server -m /Users/liwenbo/models/qwen/Qwen2.5-1.5B-Instruct.Q4_K_M.gguf
dyld[18622]: Library not loaded: @rpath/libllama.dylib
Referenced from: <A6F705D2-0AC3-32BD-8CF2-3A55262E9195> /Users/liwenbo/Downloads/4409-llamacpp/bin/llama-server
Reason: tried: '/Users/runner/work/llama.cpp/llama.cpp/build/src/libllama.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/Users/runner/work/llama.cpp/llama.cpp/build/src/libllama.dylib' (no such file), '/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/libllama.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/libllama.dylib' (no such file), '/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-blas/libllama.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-blas/libllama.dylib' (no such file), '/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-metal/libllama.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-metal/libllama.dylib' (no such file), '/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-rpc/libllama.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-rpc/libllama.dylib' (no such file), '/Users/runner/work/llama.cpp/llama.cpp/build/src/libllama.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/Users/runner/work/llama.cpp/llama.cpp/build/src/libllama.dylib' (no such file), '/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/libllama.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/libllama.dylib' (no such file), '/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-blas/libllama.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-blas/libllama.dylib' (no such file), '/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-metal/libllama.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-metal/libllama.dylib' (no such file), '/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-rpc/libllama.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/Users/runner/work/llama.cpp/llama.cpp/build/ggml/src/ggml-rpc/libllama.dylib' (no such file)
zsh: abort /Users/liwenbo/Downloads/4409-llamacpp/bin/llama-server -m
4406 run log:
/Users/liwenbo/Downloads/4406-llamacpp/bin/llama-server -m /Users/liwenbo/models/qwen/Qwen2.5-1.5B-Instruct.Q4_K_M.gguf
build: 4406 (0da5d860) with Apple clang version 15.0.0 (clang-1500.3.9.4) for arm64-apple-darwin23.6.0
system info: n_threads = 4, n_threads_batch = 4, total_threads = 10
system_info: n_threads = 4 (n_threads_batch = 4) / 10 | Metal : EMBED_LIBRARY = 1 | BF16 = 1 | CPU : NEON = 1 | ARM_FMA = 1 | FP16_VA = 1 | DOTPROD = 1 | LLAMAFILE = 1 | ACCELERATE = 1 | AARCH64_REPACK = 1 |
main: HTTP server is listening, hostname: 127.0.0.1, port: 8080, http threads: 9
main: loading model
srv load_model: loading model '/Users/liwenbo/models/qwen/Qwen2.5-1.5B-Instruct.Q4_K_M.gguf'
llama_load_model_from_file: using device Metal (Apple M4) - 10922 MiB free
llama_model_loader: loaded meta data with 32 key-value pairs and 338 tensors from /Users/liwenbo/models/qwen/Qwen2.5-1.5B-Instruct.Q4_K_M.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 = qwen2
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Models
llama_model_loader: - kv 3: general.size_label str = 1.5B
llama_model_loader: - kv 4: general.license str = apache-2.0
llama_model_loader: - kv 5: general.license.link str = https://huggingface.co/Qwen/Qwen2.5-1...
llama_model_loader: - kv 6: general.base_model.count u32 = 1
llama_model_loader: - kv 7: general.base_model.0.name str = Qwen2.5 1.5B
llama_model_loader: - kv 8: general.base_model.0.organization str = Qwen
llama_model_loader: - kv 9: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen2.5-1.5B
llama_model_loader: - kv 10: general.tags arr[str,2] = ["chat", "text-generation"]
llama_model_loader: - kv 11: general.languages arr[str,1] = ["en"]
llama_model_loader: - kv 12: qwen2.block_count u32 = 28
llama_model_loader: - kv 13: qwen2.context_length u32 = 32768
llama_model_loader: - kv 14: qwen2.embedding_length u32 = 1536
llama_model_loader: - kv 15: qwen2.feed_forward_length u32 = 8960
llama_model_loader: - kv 16: qwen2.attention.head_count u32 = 12
llama_model_loader: - kv 17: qwen2.attention.head_count_kv u32 = 2
llama_model_loader: - kv 18: qwen2.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 19: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 20: general.file_type u32 = 15
llama_model_loader: - kv 21: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 22: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 23: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 24: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 25: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 26: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 27: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 28: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 29: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 30: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 31: general.quantization_version u32 = 2
llama_model_loader: - type f32: 141 tensors
llama_model_loader: - type q4_K: 168 tensors
llama_model_loader: - type q6_K: 29 tensors
llm_load_vocab: special tokens cache size = 22
llm_load_vocab: token to piece cache size = 0.9310 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = qwen2
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 151936
llm_load_print_meta: n_merges = 151387
llm_load_print_meta: vocab_only = 0
llm_load_print_meta: n_ctx_train = 32768
llm_load_print_meta: n_embd = 1536
llm_load_print_meta: n_layer = 28
llm_load_print_meta: n_head = 12
llm_load_print_meta: n_head_kv = 2
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 = 6
llm_load_print_meta: n_embd_k_gqa = 256
llm_load_print_meta: n_embd_v_gqa = 256
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 = 8960
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 = 2
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_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: ssm_dt_b_c_rms = 0
llm_load_print_meta: model type = 1.5B
llm_load_print_meta: model ftype = Q4_K - Medium
llm_load_print_meta: model params = 1.54 B
llm_load_print_meta: model size = 934.69 MiB (5.08 BPW)
llm_load_print_meta: general.name = Models
llm_load_print_meta: BOS token = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token = 151645 '<|im_end|>'
llm_load_print_meta: EOT token = 151645 '<|im_end|>'
llm_load_print_meta: PAD token = 151643 '<|endoftext|>'
llm_load_print_meta: LF token = 148848 'ÄĬ'
llm_load_print_meta: FIM PRE token = 151659 '<|fim_prefix|>'
llm_load_print_meta: FIM SUF token = 151661 '<|fim_suffix|>'
llm_load_print_meta: FIM MID token = 151660 '<|fim_middle|>'
llm_load_print_meta: FIM PAD token = 151662 '<|fim_pad|>'
llm_load_print_meta: FIM REP token = 151663 '<|repo_name|>'
llm_load_print_meta: FIM SEP token = 151664 '<|file_sep|>'
llm_load_print_meta: EOG token = 151643 '<|endoftext|>'
llm_load_print_meta: EOG token = 151645 '<|im_end|>'
llm_load_print_meta: EOG token = 151662 '<|fim_pad|>'
llm_load_print_meta: EOG token = 151663 '<|repo_name|>'
llm_load_print_meta: EOG token = 151664 '<|file_sep|>'
llm_load_print_meta: max token length = 256
llm_load_tensors: offloading 28 repeating layers to GPU
llm_load_tensors: offloading output layer to GPU
llm_load_tensors: offloaded 29/29 layers to GPU
llm_load_tensors: Metal_Mapped model buffer size = 934.70 MiB
llm_load_tensors: CPU_Mapped model buffer size = 182.57 MiB
.....................................................................
llama_new_context_with_model: n_seq_max = 1
llama_new_context_with_model: n_ctx = 4096
llama_new_context_with_model: n_ctx_per_seq = 4096
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 = 1000000.0
llama_new_context_with_model: freq_scale = 1
llama_new_context_with_model: n_ctx_per_seq (4096) < n_ctx_train (32768) -- the full capacity of the model will not be utilized
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M4
ggml_metal_init: picking default device: Apple M4
ggml_metal_init: using embedded metal library
ggml_metal_init: GPU name: Apple M4
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 = true
ggml_metal_init: simdgroup matrix mul. = true
ggml_metal_init: has bfloat = true
ggml_metal_init: use bfloat = true
ggml_metal_init: hasUnifiedMemory = true
ggml_metal_init: recommendedMaxWorkingSetSize = 11453.25 MB
llama_kv_cache_init: kv_size = 4096, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 28
llama_kv_cache_init: Metal KV buffer size = 112.00 MiB
llama_new_context_with_model: KV self size = 112.00 MiB, K (f16): 56.00 MiB, V (f16): 56.00 MiB
llama_new_context_with_model: CPU output buffer size = 0.58 MiB
llama_new_context_with_model: Metal compute buffer size = 299.75 MiB
llama_new_context_with_model: CPU compute buffer size = 11.01 MiB
llama_new_context_with_model: graph nodes = 986
llama_new_context_with_model: graph splits = 2
common_init_from_params: setting dry_penalty_last_n to ctx_size = 4096
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
srv init: initializing slots, n_slots = 1
slot init: id 0 | task -1 | new slot n_ctx_slot = 4096
main: model loaded
main: chat template, chat_template: (built-in), example_format: '<|im_start|>system
You are a helpful assistant<|im_end|>
<|im_start|>user
Hello<|im_end|>
<|im_start|>assistant
Hi there<|im_end|>
<|im_start|>user
How are you?<|im_end|>
<|im_start|>assistant
'
main: server is listening on http://127.0.0.1:8080 - starting the main loop
srv update_slots: all slots are idle
^C
First Bad Commit
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Relevant log output
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