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[GH-ISSUE #7255] ollama run nemotron fails #51122

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opened 2026-04-28 18:28:27 -05:00 by GiteaMirror · 8 comments
GiteaMirror commented 2026-04-28 18:28:27 -05:00
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Originally created by @noskill on GitHub (Oct 18, 2024).
Original GitHub issue: https://github.com/ollama/ollama/issues/7255

What is the issue?

Error: llama runner process has terminated: signal: aborted

logs:

llama_model_load: error loading model: done_getting_tensors: wrong number of tensors; expected 724, got 723
llama_load_model_from_file: exception loading model
terminate called after throwing an instance of 'std::runtime_error'
  what():  done_getting_tensors: wrong number of tensors; expected 724, got 723
time=2024-10-18T16:54:33.575Z level=ERROR source=sched.go:344 msg="error loading llama server" error="llama runner process has terminated: signal: aborted (core dumped) "

OS

Linux ubuntu 22.04

GPU

ggml_cuda_init: found 4 CUDA devices:
  Device 0: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
  Device 1: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
  Device 2: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
  Device 3: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes

CPU

Intel

Ollama version

0.1.32

Originally created by @noskill on GitHub (Oct 18, 2024). Original GitHub issue: https://github.com/ollama/ollama/issues/7255 ### What is the issue? Error: llama runner process has terminated: signal: aborted logs: ``` llama_model_load: error loading model: done_getting_tensors: wrong number of tensors; expected 724, got 723 llama_load_model_from_file: exception loading model terminate called after throwing an instance of 'std::runtime_error' what(): done_getting_tensors: wrong number of tensors; expected 724, got 723 time=2024-10-18T16:54:33.575Z level=ERROR source=sched.go:344 msg="error loading llama server" error="llama runner process has terminated: signal: aborted (core dumped) " ``` ### OS Linux ubuntu 22.04 ### GPU ``` ggml_cuda_init: found 4 CUDA devices: Device 0: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes Device 1: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes Device 2: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes Device 3: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes ``` ### CPU Intel ### Ollama version 0.1.32
GiteaMirror added the bug label 2026-04-28 18:28:27 -05:00
GiteaMirror commented 2026-04-28 18:29:24 -05:00
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@nickpoorman commented on GitHub (Oct 18, 2024):

Also having problems running this model. Is it that my machine simply can't run a model of this size?

❯ ollama run nemotron
Error: llama runner process has terminated: signal: killed

❯ cat ~/.ollama/logs/server.log

[GIN] 2024/10/18 - 11:09:09 | 200 |      26.209µs |       127.0.0.1 | HEAD     "/"
[GIN] 2024/10/18 - 11:09:09 | 200 |   29.998666ms |       127.0.0.1 | POST     "/api/show"
time=2024-10-18T11:09:09.594-06:00 level=INFO source=server.go:108 msg="system memory" total="16.0 GiB" free="9.4 GiB" free_swap="0 B"
time=2024-10-18T11:09:09.595-06:00 level=INFO source=memory.go:326 msg="offload to metal" layers.requested=-1 layers.model=81 layers.offload=18 layers.split="" memory.available="[10.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="43.0 GiB" memory.required.partial="10.2 GiB" memory.required.kv="640.0 MiB" memory.required.allocations="[10.2 GiB]" memory.weights.total="38.9 GiB" memory.weights.repeating="38.1 GiB" memory.weights.nonrepeating="822.0 MiB" memory.graph.full="324.0 MiB" memory.graph.partial="324.0 MiB"
time=2024-10-18T11:09:09.596-06:00 level=INFO source=server.go:399 msg="starting llama server" cmd="/var/folders/hw/tjv9414j03gc_4_wych_hl1w0000gn/T/ollama3923299315/runners/metal/ollama_llama_server --model /Users/nick/.ollama/models/blobs/sha256-c147388e99312d168a2c5a75d2048cd7654828c0bb9ed5f0ad1735c655aa5b45 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 18 --no-mmap --parallel 1 --port 52656"
time=2024-10-18T11:09:09.598-06:00 level=INFO source=sched.go:449 msg="loaded runners" count=1
time=2024-10-18T11:09:09.598-06:00 level=INFO source=server.go:598 msg="waiting for llama runner to start responding"
time=2024-10-18T11:09:09.598-06:00 level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server error"
INFO [main] starting c++ runner | tid="0x2048ab240" timestamp=1729271349
INFO [main] build info | build=3670 commit="8e71a7f6" tid="0x2048ab240" timestamp=1729271349
INFO [main] system info | n_threads=4 n_threads_batch=4 system_info="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 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | " tid="0x2048ab240" timestamp=1729271349 total_threads=8
INFO [main] HTTP server listening | hostname="127.0.0.1" n_threads_http="7" port="52656" tid="0x2048ab240" timestamp=1729271349
llama_model_loader: loaded meta data with 37 key-value pairs and 724 tensors from /Users/nick/.ollama/models/blobs/sha256-c147388e99312d168a2c5a75d2048cd7654828c0bb9ed5f0ad1735c655aa5b45 (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              = Llama 3.1 70B Instruct
llama_model_loader: - kv   3:                       general.organization str              = Meta Llama
llama_model_loader: - kv   4:                           general.finetune str              = Instruct
llama_model_loader: - kv   5:                           general.basename str              = Llama-3.1
llama_model_loader: - kv   6:                         general.size_label str              = 70B
llama_model_loader: - kv   7:                            general.license str              = llama3.1
llama_model_loader: - kv   8:                   general.base_model.count u32              = 1
llama_model_loader: - kv   9:                  general.base_model.0.name str              = Llama 3.1 70B Instruct
llama_model_loader: - kv  10:          general.base_model.0.organization str              = Meta Llama
llama_model_loader: - kv  11:              general.base_model.0.repo_url str              = https://huggingface.co/meta-llama/Lla...
llama_model_loader: - kv  12:                               general.tags arr[str,3]       = ["nvidia", "llama3.1", "text-generati...
llama_model_loader: - kv  13:                          general.languages arr[str,1]       = ["en"]
llama_model_loader: - kv  14:                           general.datasets arr[str,1]       = ["nvidia/HelpSteer2"]
llama_model_loader: - kv  15:                          llama.block_count u32              = 80
llama_model_loader: - kv  16:                       llama.context_length u32              = 131072
llama_model_loader: - kv  17:                     llama.embedding_length u32              = 8192
llama_model_loader: - kv  18:                  llama.feed_forward_length u32              = 28672
llama_model_loader: - kv  19:                 llama.attention.head_count u32              = 64
llama_model_loader: - kv  20:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv  21:                       llama.rope.freq_base f32              = 500000.000000
llama_model_loader: - kv  22:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  23:                 llama.attention.key_length u32              = 128
llama_model_loader: - kv  24:               llama.attention.value_length u32              = 128
llama_model_loader: - kv  25:                          general.file_type u32              = 15
llama_model_loader: - kv  26:                           llama.vocab_size u32              = 128256
llama_model_loader: - kv  27:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  28:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  29:                         tokenizer.ggml.pre str              = llama-bpe
llama_model_loader: - kv  30:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  31:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  32:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv  33:                tokenizer.ggml.bos_token_id u32              = 128000
llama_model_loader: - kv  34:                tokenizer.ggml.eos_token_id u32              = 128009
llama_model_loader: - kv  35:                    tokenizer.chat_template str              = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv  36:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  162 tensors
llama_model_loader: - type q4_K:  441 tensors
llama_model_loader: - type q5_K:   40 tensors
llama_model_loader: - type q6_K:   81 tensors
time=2024-10-18T11:09:09.849-06:00 level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server loading model"
llm_load_vocab: special tokens cache size = 256
llm_load_vocab: token to piece cache size = 0.7999 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      = 131072
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  = 500000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn  = 131072
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       = 70B
llm_load_print_meta: model ftype      = Q4_K - Medium
llm_load_print_meta: model params     = 70.55 B
llm_load_print_meta: model size       = 39.59 GiB (4.82 BPW)
llm_load_print_meta: general.name     = Llama 3.1 70B Instruct
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
llm_load_tensors: ggml ctx size =    0.68 MiB
llm_load_tensors: offloading 18 repeating layers to GPU
llm_load_tensors: offloaded 18/81 layers to GPU
llm_load_tensors:        CPU buffer size = 31497.44 MiB
llm_load_tensors:      Metal buffer size =  9045.69 MiB
llama_new_context_with_model: n_ctx      = 2048
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  = 500000.0
llama_new_context_with_model: freq_scale = 1
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: using embedded metal library
ggml_metal_init: GPU name:   Apple M1
ggml_metal_init: GPU family: MTLGPUFamilyApple7  (1007)
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  = 11453.25 MB
time=2024-10-18T11:09:45.709-06:00 level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server not responding"
time=2024-10-18T11:09:45.985-06:00 level=ERROR source=sched.go:455 msg="error loading llama server" error="llama runner process has terminated: signal: killed"
[GIN] 2024/10/18 - 11:09:46 | 500 | 36.462390459s |       127.0.0.1 | POST     "/api/generate"

❯ sw_vers
ProductName:            macOS
ProductVersion:         15.0.1
BuildVersion:           24A348

❯ uname -a
Darwin mbp-m1 24.0.0 Darwin Kernel Version 24.0.0: Tue Sep 24 23:36:26 PDT 2024; root:xnu-11215.1.12~1/RELEASE_ARM64_T8103 arm64

❯ system_profiler SPHardwareDataType
Hardware:

    Hardware Overview:

      Model Name: MacBook Pro
      Model Identifier: MacBookPro17,1
      Model Number: MJ123LL/A
      Chip: Apple M1
      Total Number of Cores: 8 (4 performance and 4 efficiency)
      Memory: 16 GB
      System Firmware Version: 11881.1.1
      OS Loader Version: 11881.1.1


❯ sysctl -n machdep.cpu.brand_string
Apple M1

❯ vm_stat
Mach Virtual Memory Statistics: (page size of 16384 bytes)
Pages free:                              355378.
Pages active:                            222569.
Pages inactive:                          166967.
Pages speculative:                        56413.
Pages throttled:                              0.
Pages wired down:                        143109.
Pages purgeable:                           3946.
"Translation faults":                 587255247.
Pages copy-on-write:                   34600275.
Pages zero filled:                    362639528.
Pages reactivated:                     25894941.
Pages purged:                           4050873.
File-backed pages:                       148451.
Anonymous pages:                         297498.
Pages stored in compressor:              950231.
Pages occupied by compressor:             55586.
Decompressions:                        17560851.
Compressions:                          29079259.
Pageins:                               18811038.
Pageouts:                               1571431.
Swapins:                                 729059.
Swapouts:                               6987980.
<!-- gh-comment-id:2422911853 --> @nickpoorman commented on GitHub (Oct 18, 2024): Also having problems running this model. Is it that my machine simply can't run a model of this size? ``` ❯ ollama run nemotron Error: llama runner process has terminated: signal: killed ❯ cat ~/.ollama/logs/server.log [GIN] 2024/10/18 - 11:09:09 | 200 | 26.209µs | 127.0.0.1 | HEAD "/" [GIN] 2024/10/18 - 11:09:09 | 200 | 29.998666ms | 127.0.0.1 | POST "/api/show" time=2024-10-18T11:09:09.594-06:00 level=INFO source=server.go:108 msg="system memory" total="16.0 GiB" free="9.4 GiB" free_swap="0 B" time=2024-10-18T11:09:09.595-06:00 level=INFO source=memory.go:326 msg="offload to metal" layers.requested=-1 layers.model=81 layers.offload=18 layers.split="" memory.available="[10.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="43.0 GiB" memory.required.partial="10.2 GiB" memory.required.kv="640.0 MiB" memory.required.allocations="[10.2 GiB]" memory.weights.total="38.9 GiB" memory.weights.repeating="38.1 GiB" memory.weights.nonrepeating="822.0 MiB" memory.graph.full="324.0 MiB" memory.graph.partial="324.0 MiB" time=2024-10-18T11:09:09.596-06:00 level=INFO source=server.go:399 msg="starting llama server" cmd="/var/folders/hw/tjv9414j03gc_4_wych_hl1w0000gn/T/ollama3923299315/runners/metal/ollama_llama_server --model /Users/nick/.ollama/models/blobs/sha256-c147388e99312d168a2c5a75d2048cd7654828c0bb9ed5f0ad1735c655aa5b45 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 18 --no-mmap --parallel 1 --port 52656" time=2024-10-18T11:09:09.598-06:00 level=INFO source=sched.go:449 msg="loaded runners" count=1 time=2024-10-18T11:09:09.598-06:00 level=INFO source=server.go:598 msg="waiting for llama runner to start responding" time=2024-10-18T11:09:09.598-06:00 level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server error" INFO [main] starting c++ runner | tid="0x2048ab240" timestamp=1729271349 INFO [main] build info | build=3670 commit="8e71a7f6" tid="0x2048ab240" timestamp=1729271349 INFO [main] system info | n_threads=4 n_threads_batch=4 system_info="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 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | " tid="0x2048ab240" timestamp=1729271349 total_threads=8 INFO [main] HTTP server listening | hostname="127.0.0.1" n_threads_http="7" port="52656" tid="0x2048ab240" timestamp=1729271349 llama_model_loader: loaded meta data with 37 key-value pairs and 724 tensors from /Users/nick/.ollama/models/blobs/sha256-c147388e99312d168a2c5a75d2048cd7654828c0bb9ed5f0ad1735c655aa5b45 (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 = Llama 3.1 70B Instruct llama_model_loader: - kv 3: general.organization str = Meta Llama llama_model_loader: - kv 4: general.finetune str = Instruct llama_model_loader: - kv 5: general.basename str = Llama-3.1 llama_model_loader: - kv 6: general.size_label str = 70B llama_model_loader: - kv 7: general.license str = llama3.1 llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Llama 3.1 70B Instruct llama_model_loader: - kv 10: general.base_model.0.organization str = Meta Llama llama_model_loader: - kv 11: general.base_model.0.repo_url str = https://huggingface.co/meta-llama/Lla... llama_model_loader: - kv 12: general.tags arr[str,3] = ["nvidia", "llama3.1", "text-generati... llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: general.datasets arr[str,1] = ["nvidia/HelpSteer2"] llama_model_loader: - kv 15: llama.block_count u32 = 80 llama_model_loader: - kv 16: llama.context_length u32 = 131072 llama_model_loader: - kv 17: llama.embedding_length u32 = 8192 llama_model_loader: - kv 18: llama.feed_forward_length u32 = 28672 llama_model_loader: - kv 19: llama.attention.head_count u32 = 64 llama_model_loader: - kv 20: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 21: llama.rope.freq_base f32 = 500000.000000 llama_model_loader: - kv 22: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 23: llama.attention.key_length u32 = 128 llama_model_loader: - kv 24: llama.attention.value_length u32 = 128 llama_model_loader: - kv 25: general.file_type u32 = 15 llama_model_loader: - kv 26: llama.vocab_size u32 = 128256 llama_model_loader: - kv 27: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 28: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 29: tokenizer.ggml.pre str = llama-bpe llama_model_loader: - kv 30: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 31: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 32: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "... llama_model_loader: - kv 33: tokenizer.ggml.bos_token_id u32 = 128000 llama_model_loader: - kv 34: tokenizer.ggml.eos_token_id u32 = 128009 llama_model_loader: - kv 35: tokenizer.chat_template str = {{- bos_token }}\n{%- if custom_tools ... llama_model_loader: - kv 36: general.quantization_version u32 = 2 llama_model_loader: - type f32: 162 tensors llama_model_loader: - type q4_K: 441 tensors llama_model_loader: - type q5_K: 40 tensors llama_model_loader: - type q6_K: 81 tensors time=2024-10-18T11:09:09.849-06:00 level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server loading model" llm_load_vocab: special tokens cache size = 256 llm_load_vocab: token to piece cache size = 0.7999 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 = 131072 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 = 500000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 131072 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 = 70B llm_load_print_meta: model ftype = Q4_K - Medium llm_load_print_meta: model params = 70.55 B llm_load_print_meta: model size = 39.59 GiB (4.82 BPW) llm_load_print_meta: general.name = Llama 3.1 70B Instruct 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 llm_load_tensors: ggml ctx size = 0.68 MiB llm_load_tensors: offloading 18 repeating layers to GPU llm_load_tensors: offloaded 18/81 layers to GPU llm_load_tensors: CPU buffer size = 31497.44 MiB llm_load_tensors: Metal buffer size = 9045.69 MiB llama_new_context_with_model: n_ctx = 2048 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 = 500000.0 llama_new_context_with_model: freq_scale = 1 ggml_metal_init: allocating ggml_metal_init: found device: Apple M1 ggml_metal_init: picking default device: Apple M1 ggml_metal_init: using embedded metal library ggml_metal_init: GPU name: Apple M1 ggml_metal_init: GPU family: MTLGPUFamilyApple7 (1007) 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 = 11453.25 MB time=2024-10-18T11:09:45.709-06:00 level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server not responding" time=2024-10-18T11:09:45.985-06:00 level=ERROR source=sched.go:455 msg="error loading llama server" error="llama runner process has terminated: signal: killed" [GIN] 2024/10/18 - 11:09:46 | 500 | 36.462390459s | 127.0.0.1 | POST "/api/generate" ❯ sw_vers ProductName: macOS ProductVersion: 15.0.1 BuildVersion: 24A348 ❯ uname -a Darwin mbp-m1 24.0.0 Darwin Kernel Version 24.0.0: Tue Sep 24 23:36:26 PDT 2024; root:xnu-11215.1.12~1/RELEASE_ARM64_T8103 arm64 ❯ system_profiler SPHardwareDataType Hardware: Hardware Overview: Model Name: MacBook Pro Model Identifier: MacBookPro17,1 Model Number: MJ123LL/A Chip: Apple M1 Total Number of Cores: 8 (4 performance and 4 efficiency) Memory: 16 GB System Firmware Version: 11881.1.1 OS Loader Version: 11881.1.1 ❯ sysctl -n machdep.cpu.brand_string Apple M1 ❯ vm_stat Mach Virtual Memory Statistics: (page size of 16384 bytes) Pages free: 355378. Pages active: 222569. Pages inactive: 166967. Pages speculative: 56413. Pages throttled: 0. Pages wired down: 143109. Pages purgeable: 3946. "Translation faults": 587255247. Pages copy-on-write: 34600275. Pages zero filled: 362639528. Pages reactivated: 25894941. Pages purged: 4050873. File-backed pages: 148451. Anonymous pages: 297498. Pages stored in compressor: 950231. Pages occupied by compressor: 55586. Decompressions: 17560851. Compressions: 29079259. Pageins: 18811038. Pageouts: 1571431. Swapins: 729059. Swapouts: 6987980. ```
GiteaMirror commented 2026-04-28 18:29:24 -05:00
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@rick-github commented on GitHub (Oct 18, 2024):

@noskill Upgrade ollama, version 0.1.32 is too old to run new models.

@nickpoorman Your problem is different, file a separate issue. Include logs that have OLLAMA_DEBUG=1 set in the server environment.

<!-- gh-comment-id:2422958486 --> @rick-github commented on GitHub (Oct 18, 2024): @noskill Upgrade ollama, version 0.1.32 is too old to run new models. @nickpoorman Your problem is different, file a separate issue. Include logs that have `OLLAMA_DEBUG=1` set in the [server environment](https://github.com/ollama/ollama/blob/main/docs/faq.md#setting-environment-variables-on-mac).
GiteaMirror commented 2026-04-28 18:29:25 -05:00
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@noskill commented on GitHub (Oct 18, 2024):

@rick-github the error is same with version 0.1.38

<!-- gh-comment-id:2422962418 --> @noskill commented on GitHub (Oct 18, 2024): @rick-github the error is same with version 0.1.38
GiteaMirror commented 2026-04-28 18:29:25 -05:00
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@rick-github commented on GitHub (Oct 18, 2024):

@noskill Upgrade ollama, version 0.1.38 is too old to run new models.

<!-- gh-comment-id:2422963328 --> @rick-github commented on GitHub (Oct 18, 2024): @noskill [Upgrade ollama](https://github.com/ollama/ollama/blob/main/docs/faq.md#how-can-i-upgrade-ollama), version 0.1.38 is too old to run new models.
GiteaMirror commented 2026-04-28 18:29:26 -05:00
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@noskill commented on GitHub (Oct 18, 2024):

0.3.13 works

<!-- gh-comment-id:2422973869 --> @noskill commented on GitHub (Oct 18, 2024): 0.3.13 works
GiteaMirror commented 2026-04-28 18:29:26 -05:00
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@turndown commented on GitHub (Oct 23, 2024):

0.3.13 works

hello，can you run x/llama3.2-vision normally？
I use 0.3.12 version ollama run x/llama3.2-vision but it occurs error. I want to know if upgrading ollama can solve it.
The version is so closed.
Could you help me test？Thank you very much.

# ollama run x/llama3.2-vision pulling manifest pulling 652e85aa1e14... 100% ▕█████████████████████████████████████████████████████████▏ 6.0 GB pulling 622429e8d318... 100% ▕█████████████████████████████████████████████████████████▏ 1.9 GB pulling 962e0f69a367... 100% ▕█████████████████████████████████████████████████████████▏ 163 B pulling dc49c86b8ebb... 100% ▕█████████████████████████████████████████████████████████▏ 30 B pulling 6a50468ba2a8... 100% ▕█████████████████████████████████████████████████████████▏ 498 B verifying sha256 digest writing manifest success Error: llama runner process has terminated: signal: aborted (core dumped)

<!-- gh-comment-id:2430835756 --> @turndown commented on GitHub (Oct 23, 2024): > 0.3.13 works hello，can you run x/llama3.2-vision normally？ I use 0.3.12 version ollama run x/llama3.2-vision but it occurs error. I want to know if upgrading ollama can solve it. The version is so closed. Could you help me test？Thank you very much. `# ollama run x/llama3.2-vision pulling manifest pulling 652e85aa1e14... 100% ▕█████████████████████████████████████████████████████████▏ 6.0 GB pulling 622429e8d318... 100% ▕█████████████████████████████████████████████████████████▏ 1.9 GB pulling 962e0f69a367... 100% ▕█████████████████████████████████████████████████████████▏ 163 B pulling dc49c86b8ebb... 100% ▕█████████████████████████████████████████████████████████▏ 30 B pulling 6a50468ba2a8... 100% ▕█████████████████████████████████████████████████████████▏ 498 B verifying sha256 digest writing manifest success Error: llama runner process has terminated: signal: aborted (core dumped) `
GiteaMirror commented 2026-04-28 18:29:27 -05:00
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@rick-github commented on GitHub (Oct 23, 2024):

Use 0.4.0 for x/llama3.2-vision.

<!-- gh-comment-id:2431189195 --> @rick-github commented on GitHub (Oct 23, 2024): Use [0.4.0](https://github.com/ollama/ollama/releases/tag/v0.4.0-rc3) for x/llama3.2-vision.
GiteaMirror commented 2026-04-28 18:29:27 -05:00
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@turndown commented on GitHub (Oct 23, 2024):

Use 0.4.0 for x/llama3.2-vision.

Thank you. I will try later.

<!-- gh-comment-id:2431317441 --> @turndown commented on GitHub (Oct 23, 2024): > Use [0.4.0](https://github.com/ollama/ollama/releases/tag/v0.4.0-rc3) for x/llama3.2-vision. Thank you. I will try later.
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