Closed
Description
Prerequisites
Please answer the following questions for yourself before submitting an issue.
- I am running the latest code. Development is very rapid so there are no tagged versions as of now.
- I carefully followed the README.md.
- I searched using keywords relevant to my issue to make sure that I am creating a new issue that is not already open (or closed).
- I reviewed the Discussions, and have a new bug or useful enhancement to share.
Expected Behavior
run model server on h100 or a100 gpu (tried both)
Current Behavior
server dies with CUDA error 716 at ggml-cuda.cu:7546: misaligned address on first incoming job
Environment and Context
Please provide detailed information about your computer setup. This is important in case the issue is not reproducible except for under certain specific conditions.
- Physical (or virtual) hardware you are using, e.g. for Linux:
$ lscpu
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
Address sizes: 46 bits physical, 57 bits virtual
CPU(s): 26
On-line CPU(s) list: 0-25
Thread(s) per core: 1
Core(s) per socket: 1
Socket(s): 26
NUMA node(s): 1
Vendor ID: GenuineIntel
CPU family: 6
Model: 143
Model name: Intel(R) Xeon(R) Platinum 8480+
Stepping: 8
CPU MHz: 2000.000
BogoMIPS: 4000.00
Virtualization: VT-x
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 832 KiB
L1i cache: 832 KiB
L2 cache: 104 MiB
L3 cache: 416 MiB
NUMA node0 CPU(s): 0-25
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Unknown: No mitigations
Vulnerability Retbleed: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; TSX disabled
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon re
p_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq vmx ssse3 fma cx16 pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c
rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbas
e tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xg
etbv1 xsaves avx_vnni avx512_bf16 wbnoinvd arat avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq
la57 rdpid bus_lock_detect cldemote movdiri movdir64b fsrm md_clear serialize tsxldtrk avx512_fp16 arch_capabilities
- Operating System, e.g. for Linux:
$ uname -a
Linux SERVER 5.15.0-73-generic #80~20.04.1-Ubuntu SMP Wed May 17 14:58:14 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux
- SDK version, e.g. for Linux:
$ python3 --version
$ make --version
$ g++ --version
ubuntu@SERVER:~$ python3 --version
Python 3.8.10
ubuntu@SERVER:~$ make --version
GNU Make 4.2.1
Built for x86_64-pc-linux-gnu
Copyright (C) 1988-2016 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.
ubuntu@SERVER:~$ g++ --version
g++ (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Copyright (C) 2019 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
Failure Information (for bugs)
Please help provide information about the failure / bug.
Steps to Reproduce
Please provide detailed steps for reproducing the issue. We are not sitting in front of your screen, so the more detail the better.
- git clone and build with
make clean && LLAMA_CUBLAS=1 make -j - starting model server with:
serve:
./llama.cpp/server \
-m ./models/models--migtissera--SynthIA-70B-v1.5-GGUF/snapshots/9553d4b0d86069f67ea926602b2d932e78da6c6c/SynthIA-70B-v1.5.q4_0.gguf \
-c 2048 \
--threads 1 \
--n-gpu-layers 83
- send first job with
test:
curl --request POST \
--url http://localhost:8080/completion \
--header "Content-Type: application/json" \
--data '{"prompt": "Building a website can be done in 10 simple steps:","n_predict": 128}'
Failure Logs
ubuntu@SERVER:~$ make serve
./llama.cpp/server \
-m ./models/models--migtissera--SynthIA-70B-v1.5-GGUF/snapshots/9553d4b0d86069f67ea926602b2d932e78da6c6c/SynthIA-70B-v1.5.q4_0.gguf \
-c 2048 \
--threads 1 \
--n-gpu-layers 83
ggml_init_cublas: GGML_CUDA_FORCE_MMQ: no
ggml_init_cublas: CUDA_USE_TENSOR_CORES: yes
ggml_init_cublas: found 1 CUDA devices:
Device 0: NVIDIA H100 PCIe, compute capability 9.0
{"timestamp":1699974633,"level":"INFO","function":"main","line":2268,"message":"build info","build":1515,"commit":"36eed0c"}
{"timestamp":1699974633,"level":"INFO","function":"main","line":2271,"message":"system info","n_threads":1,"n_threads_batch":-1,"total_threads":26,"system_info":"AVX = 1 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | "}
llama_model_loader: loaded meta data with 20 key-value pairs and 723 tensors from ./models/models--migtissera--SynthIA-70B-v1.5-GGUF/snapshots/9553d4b0d86069f67ea926602b2d932e78da6c6c/SynthIA-70B-v1.5.q4_0.gguf (version GGUF V2)
llama_model_loader: - tensor 0: token_embd.weight q4_0 [ 8192, 32000, 1, 1 ]
llama_model_loader: - tensor 1: blk.0.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 2: blk.0.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 3: blk.0.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 4: blk.0.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 5: blk.0.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 6: blk.0.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 7: blk.0.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 8: blk.0.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 9: blk.0.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 10: blk.1.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 11: blk.1.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 12: blk.1.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 13: blk.1.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 14: blk.1.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 15: blk.1.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 16: blk.1.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 17: blk.1.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 18: blk.1.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 19: blk.2.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 20: blk.2.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 21: blk.2.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 22: blk.2.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 23: blk.2.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 24: blk.2.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 25: blk.2.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 26: blk.2.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 27: blk.2.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 28: blk.3.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 29: blk.3.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 30: blk.3.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 31: blk.3.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 32: blk.3.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 33: blk.3.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 34: blk.3.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 35: blk.3.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 36: blk.3.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 37: blk.4.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 38: blk.4.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 39: blk.4.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 40: blk.4.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 41: blk.4.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 42: blk.4.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 43: blk.4.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 44: blk.4.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 45: blk.4.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 46: blk.5.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 47: blk.5.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 48: blk.5.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 49: blk.5.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 50: blk.5.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 51: blk.5.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 52: blk.5.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 53: blk.5.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 54: blk.5.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 55: blk.6.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 56: blk.6.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 57: blk.6.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 58: blk.6.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 59: blk.6.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 60: blk.6.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 61: blk.6.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 62: blk.6.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 63: blk.6.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 64: blk.7.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 65: blk.7.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 66: blk.7.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 67: blk.7.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 68: blk.7.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 69: blk.7.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 70: blk.7.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 71: blk.7.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 72: blk.7.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 73: blk.8.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 74: blk.8.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 75: blk.8.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 76: blk.8.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 77: blk.8.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 78: blk.8.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 79: blk.8.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 80: blk.8.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 81: blk.8.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 82: blk.9.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 83: blk.9.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 84: blk.9.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 85: blk.9.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 86: blk.9.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 87: blk.9.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 88: blk.9.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 89: blk.9.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 90: blk.9.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 91: blk.10.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 92: blk.10.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 93: blk.10.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 94: blk.10.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 95: blk.10.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 96: blk.10.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 97: blk.10.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 98: blk.10.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 99: blk.10.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 100: blk.11.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 101: blk.11.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 102: blk.11.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 103: blk.11.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 104: blk.11.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 105: blk.11.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 106: blk.11.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 107: blk.11.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 108: blk.11.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 109: blk.12.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 110: blk.12.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 111: blk.12.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 112: blk.12.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 113: blk.12.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 114: blk.12.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 115: blk.12.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 116: blk.12.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 117: blk.12.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 118: blk.13.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 119: blk.13.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 120: blk.13.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 121: blk.13.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 122: blk.13.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 123: blk.13.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 124: blk.13.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 125: blk.13.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 126: blk.13.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 127: blk.14.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 128: blk.14.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 129: blk.14.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 130: blk.14.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 131: blk.14.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 132: blk.14.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 133: blk.14.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 134: blk.14.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 135: blk.14.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 136: blk.15.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 137: blk.15.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 138: blk.15.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 139: blk.15.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 140: blk.15.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 141: blk.15.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 142: blk.15.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 143: blk.15.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 144: blk.15.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 145: blk.16.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 146: blk.16.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 147: blk.16.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 148: blk.16.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 149: blk.16.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 150: blk.16.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 151: blk.16.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 152: blk.16.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 153: blk.16.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 154: blk.17.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 155: blk.17.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 156: blk.17.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
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llama_model_loader: - tensor 581: blk.64.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 582: blk.64.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 583: blk.64.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 584: blk.64.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 585: blk.64.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 586: blk.65.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 587: blk.65.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 588: blk.65.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 589: blk.65.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 590: blk.65.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 591: blk.65.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 592: blk.65.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 593: blk.65.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 594: blk.65.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 595: blk.66.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 596: blk.66.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 597: blk.66.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 598: blk.66.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 599: blk.66.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 600: blk.66.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 601: blk.66.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 602: blk.66.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 603: blk.66.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 604: blk.67.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 605: blk.67.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 606: blk.67.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 607: blk.67.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 608: blk.67.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 609: blk.67.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 610: blk.67.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 611: blk.67.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 612: blk.67.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 613: blk.68.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 614: blk.68.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 615: blk.68.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 616: blk.68.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 617: blk.68.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 618: blk.68.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 619: blk.68.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 620: blk.68.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 621: blk.68.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 622: blk.69.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 623: blk.69.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 624: blk.69.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 625: blk.69.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 626: blk.69.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 627: blk.69.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 628: blk.69.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 629: blk.69.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 630: blk.69.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 631: blk.70.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 632: blk.70.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 633: blk.70.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 634: blk.70.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 635: blk.70.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 636: blk.70.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 637: blk.70.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 638: blk.70.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 639: blk.70.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 640: blk.71.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 641: blk.71.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 642: blk.71.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 643: blk.71.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 644: blk.71.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 645: blk.71.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 646: blk.71.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 647: blk.71.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 648: blk.71.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 649: blk.72.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 650: blk.72.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 651: blk.72.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 652: blk.72.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 653: blk.72.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 654: blk.72.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 655: blk.72.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 656: blk.72.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 657: blk.72.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 658: blk.73.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 659: blk.73.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 660: blk.73.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 661: blk.73.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 662: blk.73.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 663: blk.73.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 664: blk.73.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 665: blk.73.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 666: blk.73.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 667: blk.74.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 668: blk.74.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 669: blk.74.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 670: blk.74.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 671: blk.74.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 672: blk.74.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 673: blk.74.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 674: blk.74.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 675: blk.74.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 676: blk.75.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 677: blk.75.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 678: blk.75.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 679: blk.75.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 680: blk.75.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 681: blk.75.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 682: blk.75.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 683: blk.75.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 684: blk.75.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 685: blk.76.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 686: blk.76.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 687: blk.76.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 688: blk.76.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 689: blk.76.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 690: blk.76.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 691: blk.76.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 692: blk.76.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 693: blk.76.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 694: blk.77.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 695: blk.77.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 696: blk.77.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 697: blk.77.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 698: blk.77.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 699: blk.77.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 700: blk.77.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 701: blk.77.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 702: blk.77.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 703: blk.78.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 704: blk.78.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 705: blk.78.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 706: blk.78.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 707: blk.78.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 708: blk.78.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 709: blk.78.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 710: blk.78.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 711: blk.78.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 712: blk.79.attn_q.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 713: blk.79.attn_k.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 714: blk.79.attn_v.weight q4_0 [ 8192, 1024, 1, 1 ]
llama_model_loader: - tensor 715: blk.79.attn_output.weight q4_0 [ 8192, 8192, 1, 1 ]
llama_model_loader: - tensor 716: blk.79.ffn_gate.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 717: blk.79.ffn_up.weight q4_0 [ 8192, 28672, 1, 1 ]
llama_model_loader: - tensor 718: blk.79.ffn_down.weight q4_0 [ 28672, 8192, 1, 1 ]
llama_model_loader: - tensor 719: blk.79.attn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 720: blk.79.ffn_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 721: output_norm.weight f32 [ 8192, 1, 1, 1 ]
llama_model_loader: - tensor 722: output.weight q6_K [ 8192, 32000, 1, 1 ]
llama_model_loader: - kv 0: general.architecture str
llama_model_loader: - kv 1: general.name str
llama_model_loader: - kv 2: llama.context_length u32
llama_model_loader: - kv 3: llama.embedding_length u32
llama_model_loader: - kv 4: llama.block_count u32
llama_model_loader: - kv 5: llama.feed_forward_length u32
llama_model_loader: - kv 6: llama.rope.dimension_count u32
llama_model_loader: - kv 7: llama.attention.head_count u32
llama_model_loader: - kv 8: llama.attention.head_count_kv u32
llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32
llama_model_loader: - kv 10: llama.rope.freq_base f32
llama_model_loader: - kv 11: general.file_type u32
llama_model_loader: - kv 12: tokenizer.ggml.model str
llama_model_loader: - kv 13: tokenizer.ggml.tokens arr
llama_model_loader: - kv 14: tokenizer.ggml.scores arr
llama_model_loader: - kv 15: tokenizer.ggml.token_type arr
llama_model_loader: - kv 16: tokenizer.ggml.bos_token_id u32
llama_model_loader: - kv 17: tokenizer.ggml.eos_token_id u32
llama_model_loader: - kv 18: tokenizer.ggml.unknown_token_id u32
llama_model_loader: - kv 19: general.quantization_version u32
llama_model_loader: - type f32: 161 tensors
llama_model_loader: - type q4_0: 561 tensors
llama_model_loader: - type q6_K: 1 tensors
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format = GGUF V2
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = SPM
llm_load_print_meta: n_vocab = 32000
llm_load_print_meta: n_merges = 0
llm_load_print_meta: n_ctx_train = 2048
llm_load_print_meta: n_embd = 8192
llm_load_print_meta: n_head = 64
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_layer = 80
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_gqa = 8
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: n_ff = 28672
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx = 2048
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: model type = 70B
llm_load_print_meta: model ftype = mostly Q4_0
llm_load_print_meta: model params = 68.98 B
llm_load_print_meta: model size = 36.20 GiB (4.51 BPW)
llm_load_print_meta: general.name = llm
llm_load_print_meta: BOS token = 1 '<s>'
llm_load_print_meta: EOS token = 2 '</s>'
llm_load_print_meta: UNK token = 0 '<unk>'
llm_load_print_meta: LF token = 13 '<0x0A>'
llm_load_tensors: ggml ctx size = 0.26 MB
llm_load_tensors: using CUDA for GPU acceleration
llm_load_tensors: mem required = 140.89 MB
llm_load_tensors: offloading 80 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 83/83 layers to GPU
llm_load_tensors: VRAM used: 36930.11 MB
....................................................................................................
llama_new_context_with_model: n_ctx = 2048
llama_new_context_with_model: freq_base = 10000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: offloading v cache to GPU
llama_kv_cache_init: offloading k cache to GPU
llama_kv_cache_init: VRAM kv self = 640.00 MB
llama_new_context_with_model: kv self size = 640.00 MB
llama_build_graph: non-view tensors processed: 1844/1844
llama_new_context_with_model: compute buffer total size = 309.57 MB
llama_new_context_with_model: VRAM scratch buffer: 308.00 MB
llama_new_context_with_model: total VRAM used: 37878.11 MB (model: 36930.11 MB, context: 948.00 MB)
Available slots:
-> Slot 0 - max context: 2048
llama server listening at http://127.0.0.1:8080
{"timestamp":1699974639,"level":"INFO","function":"main","line":2548,"message":"HTTP server listening","hostname":"127.0.0.1","port":8080}
all slots are idle and system prompt is empty, clear the KV cache
slot 0 is processing [task id: 0]
slot 0 : kv cache rm - [0, end)
CUDA error 716 at ggml-cuda.cu:7546: misaligned address
current device: 0
make: *** [Makefile:2: serve] Error 1