llama.cpp server with LLava stuck after image is uploaded on the first question #3798

slavag · 2023-10-26T15:47:00Z

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

Please provide a detailed written description of what you were trying to do, and what you expected llama.cpp to do.

Current Behavior

Please provide a detailed written description of what llama.cpp did, instead.

Environment and Context

Running ./server -t 4 -c 4096 -ngl 50 -m /Users/slava/Documents/Development/private/AI/Models/llava1.5/ggml-model-q5_k.gguf --host 0.0.0.0 --port 8007 --mmproj /Users/slava/Documents/Development/private/AI/Models/llava1.5/mmproj-model-f16.gguf

Environment info:

Mac M1 Max 32GB

MacOS 13.6 (22G120)

llama.cpp$ git log | head -1
commit 6961c4bd0b5176e10ab03b35394f1e9eab761792

llama.cpp$ python3 --version
Python 3.11.3

llama.cpp$ make --version | head -1
GNU Make 3.81

$ md5sum ./ggml-model-q5_k.gguf 
01878e0b413786b3a2e7845689c999da  /Users/slava/Development/private/AI/Models/llava1.5/ggml-model-q5_k.gguf

Failure Information (for bugs)

The inference is stuck, no output.

Steps to Reproduce

rec.mp4

Failure Logs

Run log

{"timestamp":1698333852,"level":"INFO","function":"main","line":2213,"message":"build info","build":1428,"commit":"6961c4b"}
{"timestamp":1698333852,"level":"INFO","function":"main","line":2220,"message":"system info","n_threads":4,"n_threads_batch":-1,"total_threads":10,"system_info":"AVX = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | "}
Multi Modal Mode Enabledclip_model_load: model name:   openai/clip-vit-large-patch14-336
clip_model_load: description:  image encoder for LLaVA
clip_model_load: GGUF version: 2
clip_model_load: alignment:    32
clip_model_load: n_tensors:    377
clip_model_load: n_kv:         18
clip_model_load: ftype:        f16

clip_model_load: text_encoder:   0
clip_model_load: vision_encoder: 1
clip_model_load: llava_projector:  1
clip_model_load: model size:     595.61 MB
clip_model_load: metadata size:  0.13 MB
clip_model_load: total allocated memory: 201.27 MB
llama_model_loader: loaded meta data with 19 key-value pairs and 291 tensors from /Users/slava/Documents/Development/private/AI/Models/llava1.5/ggml-model-q5_k.gguf (version GGUF V2 (latest))
llama_model_loader: - tensor    0:                token_embd.weight q5_K     [  4096, 32000,     1,     1 ]
llama_model_loader: - tensor    1:              blk.0.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor    2:              blk.0.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor    3:              blk.0.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor    4:         blk.0.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor    5:            blk.0.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor    6:              blk.0.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor    7:            blk.0.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor    8:           blk.0.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor    9:            blk.0.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   10:              blk.1.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   11:              blk.1.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   12:              blk.1.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   13:         blk.1.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   14:            blk.1.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   15:              blk.1.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   16:            blk.1.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor   17:           blk.1.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   18:            blk.1.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   19:              blk.2.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   20:              blk.2.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   21:              blk.2.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   22:         blk.2.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   23:            blk.2.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   24:              blk.2.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   25:            blk.2.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor   26:           blk.2.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   27:            blk.2.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   28:              blk.3.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   29:              blk.3.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   30:              blk.3.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   31:         blk.3.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   32:            blk.3.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   33:              blk.3.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   34:            blk.3.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor   35:           blk.3.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   36:            blk.3.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   37:              blk.4.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   38:              blk.4.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   39:              blk.4.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   40:         blk.4.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   41:            blk.4.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   42:              blk.4.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   43:            blk.4.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor   44:           blk.4.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   45:            blk.4.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   46:              blk.5.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   47:              blk.5.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   48:              blk.5.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   49:         blk.5.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   50:            blk.5.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   51:              blk.5.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   52:            blk.5.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor   53:           blk.5.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   54:            blk.5.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   55:              blk.6.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   56:              blk.6.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   57:              blk.6.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   58:         blk.6.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   59:            blk.6.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   60:              blk.6.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   61:            blk.6.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor   62:           blk.6.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   63:            blk.6.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   64:              blk.7.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   65:              blk.7.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   66:              blk.7.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   67:         blk.7.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   68:            blk.7.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   69:              blk.7.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   70:            blk.7.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor   71:           blk.7.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   72:            blk.7.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   73:              blk.8.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   74:              blk.8.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   75:              blk.8.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   76:         blk.8.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   77:            blk.8.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   78:              blk.8.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   79:            blk.8.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor   80:           blk.8.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   81:            blk.8.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   82:              blk.9.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   83:              blk.9.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   84:              blk.9.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   85:         blk.9.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   86:            blk.9.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   87:              blk.9.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   88:            blk.9.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor   89:           blk.9.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   90:            blk.9.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   91:             blk.10.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   92:             blk.10.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   93:             blk.10.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   94:        blk.10.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   95:           blk.10.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   96:             blk.10.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor   97:           blk.10.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor   98:          blk.10.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   99:           blk.10.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  100:             blk.11.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  101:             blk.11.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  102:             blk.11.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  103:        blk.11.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  104:           blk.11.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  105:             blk.11.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  106:           blk.11.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  107:          blk.11.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  108:           blk.11.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  109:             blk.12.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  110:             blk.12.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  111:             blk.12.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  112:        blk.12.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  113:           blk.12.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  114:             blk.12.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  115:           blk.12.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  116:          blk.12.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  117:           blk.12.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  118:             blk.13.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  119:             blk.13.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  120:             blk.13.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  121:        blk.13.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  122:           blk.13.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  123:             blk.13.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  124:           blk.13.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  125:          blk.13.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  126:           blk.13.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  127:             blk.14.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  128:             blk.14.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  129:             blk.14.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  130:        blk.14.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  131:           blk.14.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  132:             blk.14.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  133:           blk.14.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  134:          blk.14.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  135:           blk.14.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  136:             blk.15.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  137:             blk.15.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  138:             blk.15.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  139:        blk.15.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  140:           blk.15.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  141:             blk.15.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  142:           blk.15.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  143:          blk.15.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  144:           blk.15.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  145:             blk.16.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  146:             blk.16.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  147:             blk.16.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  148:        blk.16.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  149:           blk.16.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  150:             blk.16.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  151:           blk.16.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  152:          blk.16.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  153:           blk.16.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  154:             blk.17.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  155:             blk.17.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  156:             blk.17.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  157:        blk.17.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  158:           blk.17.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  159:             blk.17.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  160:           blk.17.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  161:          blk.17.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  162:           blk.17.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  163:             blk.18.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  164:             blk.18.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  165:             blk.18.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  166:        blk.18.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  167:           blk.18.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  168:             blk.18.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  169:           blk.18.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  170:          blk.18.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  171:           blk.18.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  172:             blk.19.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  173:             blk.19.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  174:             blk.19.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  175:        blk.19.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  176:           blk.19.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  177:             blk.19.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  178:           blk.19.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  179:          blk.19.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  180:           blk.19.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  181:             blk.20.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  182:             blk.20.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  183:             blk.20.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  184:        blk.20.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  185:           blk.20.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  186:             blk.20.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  187:           blk.20.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  188:          blk.20.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  189:           blk.20.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  190:             blk.21.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  191:             blk.21.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  192:             blk.21.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  193:        blk.21.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  194:           blk.21.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  195:             blk.21.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  196:           blk.21.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  197:          blk.21.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  198:           blk.21.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  199:             blk.22.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  200:             blk.22.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  201:             blk.22.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  202:        blk.22.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  203:           blk.22.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  204:             blk.22.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  205:           blk.22.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  206:          blk.22.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  207:           blk.22.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  208:             blk.23.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  209:             blk.23.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  210:             blk.23.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  211:        blk.23.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  212:           blk.23.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  213:             blk.23.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  214:           blk.23.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  215:          blk.23.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  216:           blk.23.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  217:             blk.24.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  218:             blk.24.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  219:             blk.24.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  220:        blk.24.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  221:           blk.24.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  222:             blk.24.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  223:           blk.24.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  224:          blk.24.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  225:           blk.24.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  226:             blk.25.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  227:             blk.25.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  228:             blk.25.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  229:        blk.25.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  230:           blk.25.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  231:             blk.25.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  232:           blk.25.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  233:          blk.25.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  234:           blk.25.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  235:             blk.26.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  236:             blk.26.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  237:             blk.26.attn_v.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  238:        blk.26.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  239:           blk.26.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  240:             blk.26.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  241:           blk.26.ffn_down.weight q5_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  242:          blk.26.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  243:           blk.26.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  244:             blk.27.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  245:             blk.27.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  246:             blk.27.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  247:        blk.27.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  248:           blk.27.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  249:             blk.27.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  250:           blk.27.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  251:          blk.27.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  252:           blk.27.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  253:             blk.28.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  254:             blk.28.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  255:             blk.28.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  256:        blk.28.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  257:           blk.28.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  258:             blk.28.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  259:           blk.28.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  260:          blk.28.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  261:           blk.28.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  262:             blk.29.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  263:             blk.29.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  264:             blk.29.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  265:        blk.29.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  266:           blk.29.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  267:             blk.29.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  268:           blk.29.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  269:          blk.29.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  270:           blk.29.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  271:             blk.30.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  272:             blk.30.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  273:             blk.30.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  274:        blk.30.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  275:           blk.30.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  276:             blk.30.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  277:           blk.30.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  278:          blk.30.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  279:           blk.30.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  280:             blk.31.attn_q.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  281:             blk.31.attn_k.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  282:             blk.31.attn_v.weight q6_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  283:        blk.31.attn_output.weight q5_K     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  284:           blk.31.ffn_gate.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  285:             blk.31.ffn_up.weight q5_K     [  4096, 11008,     1,     1 ]
llama_model_loader: - tensor  286:           blk.31.ffn_down.weight q6_K     [ 11008,  4096,     1,     1 ]
llama_model_loader: - tensor  287:          blk.31.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  288:           blk.31.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  289:               output_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  290:                    output.weight q6_K     [  4096, 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:                          general.file_type u32     
llama_model_loader: - kv  11:                       tokenizer.ggml.model str     
llama_model_loader: - kv  12:                      tokenizer.ggml.tokens arr     
llama_model_loader: - kv  13:                      tokenizer.ggml.scores arr     
llama_model_loader: - kv  14:                  tokenizer.ggml.token_type arr     
llama_model_loader: - kv  15:                tokenizer.ggml.bos_token_id u32     
llama_model_loader: - kv  16:                tokenizer.ggml.eos_token_id u32     
llama_model_loader: - kv  17:            tokenizer.ggml.padding_token_id u32     
llama_model_loader: - kv  18:               general.quantization_version u32     
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q5_K:  193 tensors
llama_model_loader: - type q6_K:   33 tensors
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format           = GGUF V2 (latest)
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      = 4096
llm_load_print_meta: n_embd           = 4096
llm_load_print_meta: n_head           = 32
llm_load_print_meta: n_head_kv        = 32
llm_load_print_meta: n_layer          = 32
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_gqa            = 1
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             = 11008
llm_load_print_meta: freq_base_train  = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: model type       = 7B
llm_load_print_meta: model ftype      = mostly Q5_K - Medium
llm_load_print_meta: model params     = 6.74 B
llm_load_print_meta: model size       = 4.45 GiB (5.68 BPW) 
llm_load_print_meta: general.name   = LLaMA v2
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: PAD token = 0 '<unk>'
llm_load_print_meta: LF token  = 13 '<0x0A>'
llm_load_tensors: ggml ctx size =    0.10 MB
llm_load_tensors: mem required  = 4560.96 MB
..................................................................................................
llama_new_context_with_model: n_ctx      = 4096
llama_new_context_with_model: freq_base  = 10000.0
llama_new_context_with_model: freq_scale = 1
llama_new_context_with_model: kv self size  = 2048.00 MB
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1 Max
ggml_metal_init: picking default device: Apple M1 Max
ggml_metal_init: default.metallib not found, loading from source
ggml_metal_init: loading '/Users/slava/Documents/Development/private/AI/llama.cpp/ggml-metal.metal'
ggml_metal_init: loaded kernel_add                            0x104204b40 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_add_row                        0x12a706f50 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul                            0x12b105c30 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_row                        0x12b106330 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_scale                          0x12b106870 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_scale_4                        0x104205280 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_silu                           0x1042058e0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_relu                           0x12a604e40 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_gelu                           0x12a707490 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_soft_max                       0x12a707c50 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_soft_max_4                     0x104205d00 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_diag_mask_inf                  0x1042064f0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_diag_mask_inf_8                0x104206b70 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_f32                   0x104207240 | th_max =  896 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_f16                   0x104207910 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q4_0                  0x104207fe0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q4_1                  0x1042086b0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q5_0                  0x12b106e20 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q5_1                  0x12b107610 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q8_0                  0x12b107f70 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q2_K                  0x12b108640 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q3_K                  0x12b108d10 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q4_K                  0x12b1093e0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q5_K                  0x104208de0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_get_rows_q6_K                  0x1042094b0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_rms_norm                       0x104209b90 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_norm                           0x10420a260 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_f32_f32                 0x10420a9a0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_f16_f32                 0x10420b220 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_f16_f32_1row            0x10420baa0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_f16_f32_l4              0x12b109da0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_q4_0_f32                0x12b10a640 | th_max =  896 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_q4_1_f32                0x12b10ab80 | th_max =  896 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_q5_0_f32                0x10420c100 | th_max =  576 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_q5_1_f32                0x10420c9a0 | th_max =  576 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_q8_0_f32                0x12a708870 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_q2_K_f32                0x12b004bc0 | th_max =  640 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_q3_K_f32                0x12b006370 | th_max =  576 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_q4_K_f32                0x12b006a50 | th_max =  576 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_q5_K_f32                0x12b0071d0 | th_max =  640 | th_width =   32
ggml_metal_init: loaded kernel_mul_mv_q6_K_f32                0x10420d000 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_f32_f32                 0x12a605950 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_f16_f32                 0x10420d670 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q4_0_f32                0x12a708ff0 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q4_1_f32                0x10420e190 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q5_0_f32                0x12b10afa0 | th_max =  704 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q5_1_f32                0x12b10bb50 | th_max =  704 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q8_0_f32                0x12b10c690 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q2_K_f32                0x12b10cec0 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q3_K_f32                0x12b10d6f0 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q4_K_f32                0x12b10df20 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q5_K_f32                0x12b10e750 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_mul_mm_q6_K_f32                0x10420ecb0 | th_max =  768 | th_width =   32
ggml_metal_init: loaded kernel_rope_f32                       0x10420f1f0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_rope_f16                       0x10420f730 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_alibi_f32                      0x10420fc70 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_cpy_f32_f16                    0x12a6060e0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_cpy_f32_f32                    0x12a606ab0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_cpy_f16_f16                    0x1041054b0 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_concat                         0x104105950 | th_max = 1024 | th_width =   32
ggml_metal_init: loaded kernel_sqr                            0x104105e90 | th_max = 1024 | th_width =   32
ggml_metal_init: GPU name:   Apple M1 Max
ggml_metal_init: GPU family: MTLGPUFamilyApple7 (1007)
ggml_metal_init: hasUnifiedMemory              = true
ggml_metal_init: recommendedMaxWorkingSetSize  = 21845.34 MB
ggml_metal_init: maxTransferRate               = built-in GPU
llama_new_context_with_model: compute buffer total size = 294.13 MB
llama_new_context_with_model: max tensor size =   102.54 MB
ggml_metal_add_buffer: allocated 'data            ' buffer, size =  4561.58 MB, ( 4562.08 / 21845.34)
ggml_metal_add_buffer: allocated 'kv              ' buffer, size =  2048.02 MB, ( 6610.09 / 21845.34)
ggml_metal_add_buffer: allocated 'alloc           ' buffer, size =   288.02 MB, ( 6898.11 / 21845.34)
Available slots:
 -> Slot 0 - max context: 4096

llama server listening at http://0.0.0.0:8007

{"timestamp":1698333859,"level":"INFO","function":"main","line":2495,"message":"HTTP server listening","hostname":"0.0.0.0","port":8007}
all slots are idle and system prompt is empty, clear the KV cache
{"timestamp":1698333903,"level":"INFO","function":"log_server_request","line":2163,"message":"request","remote_addr":"127.0.0.1","remote_port":61738,"status":200,"method":"GET","path":"/","params":{}}
{"timestamp":1698333903,"level":"INFO","function":"log_server_request","line":2163,"message":"request","remote_addr":"127.0.0.1","remote_port":61740,"status":200,"method":"GET","path":"/completion.js","params":{}}
{"timestamp":1698333903,"level":"INFO","function":"log_server_request","line":2163,"message":"request","remote_addr":"127.0.0.1","remote_port":61742,"status":200,"method":"GET","path":"/json-schema-to-grammar.mjs","params":{}}
{"timestamp":1698333903,"level":"INFO","function":"log_server_request","line":2163,"message":"request","remote_addr":"127.0.0.1","remote_port":61738,"status":200,"method":"GET","path":"/index.js","params":{}}
{"timestamp":1698333903,"level":"INFO","function":"log_server_request","line":2163,"message":"request","remote_addr":"127.0.0.1","remote_port":61740,"status":404,"method":"GET","path":"/favicon.ico","params":{}}
slot 0 - image loaded [id: 10] resolution (1200 x 1800)
slot 0 is processing [task id: 0]

print_timings: prompt eval time =       0.00 ms /     0 tokens (     nan ms per token,      nan tokens per second)
print_timings:        eval time = 2427173839.78 ms /     0 runs   (     inf ms per token,     0.00 tokens per second)
print_timings:       total time = 2427173839.78 ms
{"timestamp":1698334323,"level":"INFO","function":"log_server_request","line":2163,"message":"request","remote_addr":"127.0.0.1","remote_port":61831,"status":200,"method":"POST","path":"/completion","params":{}}
slot 0 released (0 tokens in cache)
slot 0 released (0 tokens in cache)

The text was updated successfully, but these errors were encountered:

abeiro · 2023-10-26T19:42:32Z

Same issue here:

Using server API directly, this is the log.

  "timestamp": 1698349120,
  "level": "VERBOSE",
  "function": "log_server_request",
  "line": 2165,
  "message": "request",
  "request": "{\"prompt\":\"USER:[img-1]Describe the image in detail.\\\\nASSISTANT:\",\"n_predict\":128,\"image_data\":[{\"data\":\"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\",\"id\":1}],\"ignore_eos\":true}",
  "response": "{\"content\":\"\",\"generation_settings\":{\"frequency_penalty\":0.0,\"grammar\":\"\",\"ignore_eos\":true,\"logit_bias\":[[2,null]],\"mirostat\":0,\"mirostat_eta\":0.10000000149011612,\"mirostat_tau\":5.0,\"model\":\"../models/ggml-model-q4_k.gguf\",\"n_ctx\":4096,\"n_keep\":0,\"n_predict\":128,\"n_probs\":0,\"penalize_nl\":true,\"presence_penalty\":0.0,\"repeat_last_n\":64,\"repeat_penalty\":1.100000023841858,\"seed\":4294967295,\"stop\":[],\"stream\":false,\"temp\":0.800000011920929,\"tfs_z\":1.0,\"top_k\":40,\"top_p\":0.949999988079071,\"typical_p\":1.0},\"model\":\"../models/ggml-model-q4_k.gguf\",\"prompt\":\"\",\"slot_id\":0,\"stop\":true,\"stopped_eos\":false,\"stopped_limit\":false,\"stopped_word\":false,\"stopping_word\":\"\",\"timings\":{\"predicted_ms\":455746.795,\"predicted_n\":54,\"predicted_per_second\":0.11848684531067301,\"predicted_per_token_ms\":8439.755462962963,\"prompt_ms\":168.66,\"prompt_n\":53,\"prompt_per_second\":314.24166963121075,\"prompt_per_token_ms\":3.182264150943396},\"tokens_cached\":0,\"tokens_evaluated\":0,\"tokens_predicted\":54,\"truncated\":false}"
}

Using server API directly, just omitting the image_data parameter, works.this is the log.

{
  "timestamp": 1698349130,
  "level": "VERBOSE",
  "function": "log_server_request",
  "line": 2165,
  "message": "request",
  "request": "{\"prompt\":\"USER:[img-1]Describe the image in detail.\\\\nASSISTANT:\",\"n_predict\":128,\"ignore_eos\":true}",
  "response": "{\"content\":\" The image captures a scene at the beach where multiple people are enjoying themselves in the water.\\nThere are several individuals scattered around the area, with some closer to the water's edge and others further out towards the sea. Some of them have their surfboards nearby, preparing for a day of surfing or taking a break from their activities. One person can be seen carrying a backpack while they engage in water sports.\\nThe atmosphere seems relaxed and fun as people spend time together at this popular beach spot. Overall, it's a lively scene that showcases the joyful side of le\",\"generation_settings\":{\"frequency_penalty\":0.0,\"grammar\":\"\",\"ignore_eos\":true,\"logit_bias\":[[2,null]],\"mirostat\":0,\"mirostat_eta\":0.10000000149011612,\"mirostat_tau\":5.0,\"model\":\"../models/ggml-model-q4_k.gguf\",\"n_ctx\":4096,\"n_keep\":0,\"n_predict\":128,\"n_probs\":0,\"penalize_nl\":true,\"presence_penalty\":0.0,\"repeat_last_n\":64,\"repeat_penalty\":1.100000023841858,\"seed\":4294967295,\"stop\":[],\"stream\":false,\"temp\":0.800000011920929,\"tfs_z\":1.0,\"top_k\":40,\"top_p\":0.949999988079071,\"typical_p\":1.0},\"model\":\"../models/ggml-model-q4_k.gguf\",\"prompt\":\"USER:[img-1]Describe the image in detail.\\\\nASSISTANT:\",\"slot_id\":0,\"stop\":true,\"stopped_eos\":false,\"stopped_limit\":true,\"stopped_word\":false,\"stopping_word\":\"\",\"timings\":{\"predicted_ms\":2422.655,\"predicted_n\":128,\"predicted_per_second\":52.83459675438723,\"predicted_per_token_ms\":18.9269921875,\"prompt_ms\":139.984,\"prompt_n\":20,\"prompt_per_second\":142.8734712538576,\"prompt_per_token_ms\":6.9992},\"tokens_cached\":148,\"tokens_evaluated\":20,\"tokens_predicted\":128,\"truncated\":false}"
}

ggerganov · 2023-10-26T19:54:52Z

Should be fixed now

jrichey98 · 2023-10-27T02:07:27Z

Yesterday I was unable to get Llava to work with the following commands and the latest build. Just wanted to say that fixed the issue for me. Thanks!

Commands run:

$ wget https://huggingface.co/mys/ggml_llava-v1.5-7b/resolve/main/ggml-model-f16.gguf -P ./models/
$ wget https://huggingface.co/mys/ggml_llava-v1.5-7b/resolve/main/mmproj-model-f16.gguf -P ./models/
$ make clean
$ git pull
$ make LLAMA_CUBLAS=1

Yesterday:

Today:

abeiro · 2023-10-27T04:54:33Z

Working here too. Thank!

slavag · 2023-10-27T06:10:31Z

Working fine.
Thanks.

* master: (350 commits) speculative : ensure draft and target model vocab matches (ggml-org#3812) llama : correctly report GGUFv3 format (ggml-org#3818) simple : fix batch handling (ggml-org#3803) cuda : improve text-generation and batched decoding performance (ggml-org#3776) server : do not release slot on image input (ggml-org#3798) batched-bench : print params at start log : disable pid in log filenames server : add parameter -tb N, --threads-batch N (ggml-org#3584) (ggml-org#3768) server : do not block system prompt update (ggml-org#3767) sync : ggml (conv ops + cuda MSVC fixes) (ggml-org#3765) cmake : add missed dependencies (ggml-org#3763) cuda : add batched cuBLAS GEMM for faster attention (ggml-org#3749) Add more tokenizer tests (ggml-org#3742) metal : handle ggml_scale for n%4 != 0 (close ggml-org#3754) Revert "make : add optional CUDA_NATIVE_ARCH (ggml-org#2482)" issues : separate bug and enhancement template + no default title (ggml-org#3748) Update special token handling in conversion scripts for gpt2 derived tokenizers (ggml-org#3746) llama : remove token functions with `context` args in favor of `model` (ggml-org#3720) Fix baichuan convert script not detecing model (ggml-org#3739) make : add optional CUDA_NATIVE_ARCH (ggml-org#2482) ...

slavag added the bug Something isn't working label Oct 26, 2023

ggerganov added a commit that referenced this issue Oct 26, 2023

server : do not release slot on image input (#3798)

34b2a5e

slavag closed this as completed Oct 27, 2023

BobCN2017 mentioned this issue Nov 5, 2023

Multimodal Support (Llava 1.5) abetlen/llama-cpp-python#821

Merged

olexiyb pushed a commit to Sanctum-AI/llama.cpp that referenced this issue Nov 23, 2023

server : do not release slot on image input (ggml-org#3798)

73b81db

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llama.cpp server with LLava stuck after image is uploaded on the first question #3798

llama.cpp server with LLava stuck after image is uploaded on the first question #3798

slavag commented Oct 26, 2023 •

edited

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abeiro commented Oct 26, 2023

ggerganov commented Oct 26, 2023

jrichey98 commented Oct 27, 2023 •

edited

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abeiro commented Oct 27, 2023

slavag commented Oct 27, 2023

llama.cpp server with LLava stuck after image is uploaded on the first question #3798

llama.cpp server with LLava stuck after image is uploaded on the first question #3798

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slavag commented Oct 26, 2023 • edited Loading

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Expected Behavior

Current Behavior

Environment and Context

Failure Information (for bugs)

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Failure Logs

abeiro commented Oct 26, 2023

ggerganov commented Oct 26, 2023

jrichey98 commented Oct 27, 2023 • edited Loading

abeiro commented Oct 27, 2023

slavag commented Oct 27, 2023

slavag commented Oct 26, 2023 •

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jrichey98 commented Oct 27, 2023 •

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