[Baichuan2 Error] : CUDA error 9 at xxx/llama.cpp/ggml-cuda.cu:6862: invalid configuration argument

[wzp123123]

Pipeline

I try to convert baichuan2 model to gguf format and load it.

step 1. Use the Script https://github.com/baichuan-inc/Baichuan2/blob/main/README_EN.md#migrating-inference-optimizations-from-baichuan-1-to-baichuan-2 convert Baichuan2 to Baichuan1

step 2. I try to use convert.py and convert-baichuan-hf-to-gguf.py to convert baichuan1 to gguf

step 3. Use build/bin/quantize to quantize gguf model to q4_0

step 4. Use build/bin/main to run prompt.

I try both 7b-chat and 13b-chat model, convert.py and convert-baichuan-hf-to-gguf.py.

CPU works well, but GPU error, i am sure i use the latest llama.cpp version.

Log and Error Message

build/bin/main -m ../model/gguf/baichuan2-7b-chat.Q4_0.gguf --prompt "赏析：白日依山尽，黄河入海流" -ngl 1
Log start
main: build = 1414 (96981f3)
main: built with cc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 for x86_64-linux-gnu
main: seed = 1698054643
ggml_init_cublas: found 1 CUDA devices:
Device 0: Tesla T4, compute capability 7.5
llama_model_loader: loaded meta data with 20 key-value pairs and 291 tensors from ../model/gguf/baichuan2-7b-chat.Q4_0.gguf (version unknown)
llama_model_loader: - tensor 0: token_embd.weight q4_0 [ 4096, 125696, 1, 1 ]
llama_model_loader: - tensor 1: blk.0.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 2: blk.0.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 3: blk.0.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 4: blk.0.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 5: blk.0.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 6: blk.0.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 7: blk.1.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 8: blk.1.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 9: blk.1.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 10: blk.1.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 11: blk.1.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 12: blk.1.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 13: blk.2.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 14: blk.2.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 15: blk.2.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 16: blk.2.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 17: blk.2.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 18: blk.2.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 19: blk.3.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 20: blk.3.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 21: blk.3.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 22: blk.3.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 23: blk.3.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 24: blk.3.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 25: blk.4.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 26: blk.4.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 27: blk.4.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 28: blk.4.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 29: blk.4.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 30: blk.4.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 31: blk.5.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 32: blk.5.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 33: blk.5.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 34: blk.5.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 35: blk.5.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 36: blk.5.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 37: blk.6.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 38: blk.6.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 39: blk.6.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 40: blk.6.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 41: blk.6.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 42: blk.6.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 43: blk.7.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 44: blk.7.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 45: blk.7.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 46: blk.7.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 47: blk.7.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 48: blk.7.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 49: blk.8.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 50: blk.8.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 51: blk.8.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 52: blk.8.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 53: blk.8.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 54: blk.8.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 55: blk.9.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 56: blk.9.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 57: blk.9.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 58: blk.9.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 59: blk.9.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 60: blk.9.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 61: blk.10.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 62: blk.10.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 63: blk.10.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 64: blk.10.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 65: blk.10.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 66: blk.10.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 67: blk.11.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 68: blk.11.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 69: blk.11.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 70: blk.11.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 71: blk.11.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 72: blk.11.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 73: blk.12.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 74: blk.12.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 75: blk.12.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 76: blk.12.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 77: blk.12.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 78: blk.12.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 79: blk.13.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 80: blk.13.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 81: blk.13.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 82: blk.13.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 83: blk.13.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 84: blk.13.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 85: blk.14.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 86: blk.14.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 87: blk.14.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 88: blk.14.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 89: blk.14.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 90: blk.14.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 91: blk.15.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 92: blk.15.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 93: blk.15.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 94: blk.15.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 95: blk.15.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 96: blk.15.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 97: blk.16.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 98: blk.16.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 99: blk.16.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 100: blk.16.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 101: blk.16.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 102: blk.16.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 103: blk.17.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 104: blk.17.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 105: blk.17.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 106: blk.17.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 107: blk.17.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 108: blk.17.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 109: blk.18.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 110: blk.18.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 111: blk.18.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 112: blk.18.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 113: blk.18.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 114: blk.18.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 115: blk.19.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 116: blk.19.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 117: blk.19.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 118: blk.19.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 119: blk.19.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 120: blk.19.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 121: blk.20.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 122: blk.20.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 123: blk.20.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 124: blk.20.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 125: blk.20.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 126: blk.20.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 127: blk.21.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 128: blk.21.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 129: blk.21.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 130: blk.21.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 131: blk.21.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 132: blk.21.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 133: blk.22.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 134: blk.22.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 135: blk.22.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 136: blk.22.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 137: blk.22.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 138: blk.22.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 139: blk.23.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 140: blk.23.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 141: blk.23.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 142: blk.23.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 143: blk.23.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 144: blk.23.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 145: blk.24.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 146: blk.24.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 147: blk.24.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 148: blk.24.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 149: blk.24.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 150: blk.24.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 151: blk.25.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 152: blk.25.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 153: blk.25.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 154: blk.25.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 155: blk.25.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 156: blk.25.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 157: blk.26.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 158: blk.26.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 159: blk.26.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 160: blk.26.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 161: blk.26.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 162: blk.26.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 163: blk.27.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 164: blk.27.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 165: blk.27.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 166: blk.27.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 167: blk.27.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 168: blk.27.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 169: blk.28.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 170: blk.28.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 171: blk.28.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 172: blk.28.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 173: blk.28.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 174: blk.28.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 175: blk.29.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 176: blk.29.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 177: blk.29.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 178: blk.29.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 179: blk.29.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 180: blk.29.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 181: blk.30.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 182: blk.30.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 183: blk.30.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 184: blk.30.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 185: blk.30.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 186: blk.30.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 187: blk.31.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 188: blk.31.ffn_gate.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 189: blk.31.ffn_down.weight q4_0 [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 190: blk.31.ffn_up.weight q4_0 [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 191: blk.31.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 192: blk.31.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 193: output_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 194: output.weight q6_K [ 4096, 125696, 1, 1 ]
llama_model_loader: - tensor 195: blk.0.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 196: blk.0.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 197: blk.0.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 198: blk.1.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 199: blk.1.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 200: blk.1.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 201: blk.2.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 202: blk.2.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 203: blk.2.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 204: blk.3.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 205: blk.3.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 206: blk.3.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 207: blk.4.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 208: blk.4.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 209: blk.4.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 210: blk.5.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 211: blk.5.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 212: blk.5.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 213: blk.6.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 214: blk.6.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 215: blk.6.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 216: blk.7.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 217: blk.7.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 218: blk.7.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 219: blk.8.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 220: blk.8.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 221: blk.8.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 222: blk.9.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 223: blk.9.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 224: blk.9.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 225: blk.10.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 226: blk.10.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 227: blk.10.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 228: blk.11.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 229: blk.11.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 230: blk.11.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 231: blk.12.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 232: blk.12.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 233: blk.12.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 234: blk.13.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 235: blk.13.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 236: blk.13.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 237: blk.14.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 238: blk.14.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 239: blk.14.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 240: blk.15.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 241: blk.15.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 242: blk.15.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 243: blk.16.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 244: blk.16.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 245: blk.16.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 246: blk.17.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 247: blk.17.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 248: blk.17.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 249: blk.18.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 250: blk.18.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 251: blk.18.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 252: blk.19.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 253: blk.19.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 254: blk.19.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 255: blk.20.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 256: blk.20.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 257: blk.20.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 258: blk.21.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 259: blk.21.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 260: blk.21.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 261: blk.22.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 262: blk.22.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 263: blk.22.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 264: blk.23.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 265: blk.23.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 266: blk.23.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 267: blk.24.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 268: blk.24.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 269: blk.24.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 270: blk.25.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 271: blk.25.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 272: blk.25.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 273: blk.26.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 274: blk.26.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 275: blk.26.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 276: blk.27.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 277: blk.27.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 278: blk.27.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 279: blk.28.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 280: blk.28.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 281: blk.28.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 282: blk.29.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 283: blk.29.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 284: blk.29.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 285: blk.30.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 286: blk.30.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 287: blk.30.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 288: blk.31.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 289: blk.31.attn_k.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 290: blk.31.attn_v.weight q4_0 [ 4096, 4096, 1, 1 ]
llama_model_loader: - kv 0: general.architecture str
llama_model_loader: - kv 1: general.name str
llama_model_loader: - kv 2: baichuan.tensor_data_layout str
llama_model_loader: - kv 3: baichuan.context_length u32
llama_model_loader: - kv 4: baichuan.embedding_length u32
llama_model_loader: - kv 5: baichuan.block_count u32
llama_model_loader: - kv 6: baichuan.feed_forward_length u32
llama_model_loader: - kv 7: baichuan.rope.dimension_count u32
llama_model_loader: - kv 8: baichuan.attention.head_count u32
llama_model_loader: - kv 9: baichuan.attention.head_count_kv u32
llama_model_loader: - kv 10: baichuan.attention.layer_norm_rms_epsilon f32
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: - kv 19: general.file_type u32
llama_model_loader: - type f32: 65 tensors
llama_model_loader: - type q4_0: 225 tensors
llama_model_loader: - type q6_K: 1 tensors
llm_load_vocab: mismatch in special tokens definition ( 1298/125696 vs 259/125696 ).
llm_load_print_meta: format = unknown
llm_load_print_meta: arch = baichuan
llm_load_print_meta: vocab type = SPM
llm_load_print_meta: n_vocab = 125696
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-06
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: 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 Q4_0
llm_load_print_meta: model params = 7.51 B
llm_load_print_meta: model size = 4.06 GiB (4.64 BPW)
llm_load_print_meta: general.name = Baichuan2-7B-Chat
llm_load_print_meta: BOS token = 1 ''
llm_load_print_meta: EOS token = 2 ''
llm_load_print_meta: UNK token = 0 ''
llm_load_print_meta: PAD token = 0 ''
llm_load_print_meta: LF token = 1099 '<0x0A>'
llm_load_tensors: ggml ctx size = 0.10 MB
llm_load_tensors: using CUDA for GPU acceleration
llm_load_tensors: mem required = 4045.48 MB
llm_load_tensors: offloading 1 repeating layers to GPU
llm_load_tensors: offloaded 1/35 layers to GPU
llm_load_tensors: VRAM used: 108.59 MB
......................................................................................
llama_new_context_with_model: n_ctx = 512
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 = 256.00 MB
llama_new_context_with_model: compute buffer total size = 259.63 MB
llama_new_context_with_model: VRAM scratch buffer: 253.50 MB
llama_new_context_with_model: total VRAM used: 362.09 MB (model: 108.59 MB, context: 253.50 MB)

system_info: n_threads = 8 / 16 | AVX = 1 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 0 | 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 |
sampling:
repeat_last_n = 64, repeat_penalty = 1.100, frequency_penalty = 0.000, presence_penalty = 0.000
top_k = 40, tfs_z = 1.000, top_p = 0.950, typical_p = 1.000, temp = 0.800
mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
generate: n_ctx = 512, n_batch = 512, n_predict = -1, n_keep = 0

赏析：白日依山尽，黄河入海流。
CUDA error 9 at /home/ubuntu/workspace/baichuan2-gguf-sagemaker/llama.cpp/ggml-cuda.cu:6862: invalid configuration argument
current device: 0

[happyme531]

Exact same error for causallm
Maybe (not) related: #3732

/m/n/l/llama.cpp (master) [1]> ./main -ngl 999 -i -m ../../text-generation-webui/models/causallm_14b.Q5_1.gguf
Log start
main: build = 239 (96981f3)
main: built with cc (GCC) 13.2.1 20230801 for x86_64-pc-linux-gnu
main: seed  = 1698080075
ggml_init_cublas: found 1 CUDA devices:
  Device 0: NVIDIA GeForce RTX 3090, compute capability 8.6
llama_model_loader: loaded meta data with 21 key-value pairs and 363 tensors from ../../text-generation-webui/models/causallm_14b.Q5_1.gguf (version unknown)
llama_model_loader: - tensor    0:                token_embd.weight q5_1     [  5120, 152064,     1,     1 ]
llama_model_loader: - tensor    1:              blk.0.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor    2:              blk.0.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor    3:              blk.0.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor    4:         blk.0.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor    5:            blk.0.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor    6:              blk.0.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor    7:            blk.0.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor    8:           blk.0.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor    9:            blk.0.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   10:              blk.1.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   11:              blk.1.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   12:              blk.1.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   13:         blk.1.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   14:            blk.1.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   15:              blk.1.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   16:            blk.1.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor   17:           blk.1.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   18:            blk.1.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   19:              blk.2.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   20:              blk.2.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   21:              blk.2.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   22:         blk.2.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   23:            blk.2.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   24:              blk.2.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   25:            blk.2.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor   26:           blk.2.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   27:            blk.2.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   28:              blk.3.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   29:              blk.3.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   30:              blk.3.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   31:         blk.3.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   32:            blk.3.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   33:              blk.3.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   34:            blk.3.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor   35:           blk.3.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   36:            blk.3.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   37:              blk.4.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   38:              blk.4.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   39:              blk.4.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   40:         blk.4.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   41:            blk.4.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   42:              blk.4.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   43:            blk.4.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor   44:           blk.4.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   45:            blk.4.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   46:              blk.5.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   47:              blk.5.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   48:              blk.5.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   49:         blk.5.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   50:            blk.5.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   51:              blk.5.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   52:            blk.5.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor   53:           blk.5.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   54:            blk.5.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   55:              blk.6.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   56:              blk.6.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   57:              blk.6.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   58:         blk.6.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   59:            blk.6.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   60:              blk.6.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   61:            blk.6.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor   62:           blk.6.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   63:            blk.6.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   64:              blk.7.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   65:              blk.7.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   66:              blk.7.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   67:         blk.7.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   68:            blk.7.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   69:              blk.7.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   70:            blk.7.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor   71:           blk.7.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   72:            blk.7.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   73:              blk.8.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   74:              blk.8.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   75:              blk.8.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   76:         blk.8.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   77:            blk.8.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   78:              blk.8.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   79:            blk.8.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor   80:           blk.8.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   81:            blk.8.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   82:              blk.9.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   83:              blk.9.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   84:              blk.9.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   85:         blk.9.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   86:            blk.9.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   87:              blk.9.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   88:            blk.9.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor   89:           blk.9.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   90:            blk.9.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   91:             blk.10.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   92:             blk.10.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   93:             blk.10.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   94:        blk.10.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor   95:           blk.10.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   96:             blk.10.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor   97:           blk.10.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor   98:          blk.10.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor   99:           blk.10.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  100:             blk.11.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  101:             blk.11.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  102:             blk.11.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  103:        blk.11.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  104:           blk.11.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  105:             blk.11.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  106:           blk.11.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  107:          blk.11.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  108:           blk.11.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  109:             blk.12.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  110:             blk.12.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  111:             blk.12.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  112:        blk.12.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  113:           blk.12.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  114:             blk.12.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  115:           blk.12.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  116:          blk.12.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  117:           blk.12.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  118:             blk.13.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  119:             blk.13.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  120:             blk.13.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  121:        blk.13.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  122:           blk.13.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  123:             blk.13.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  124:           blk.13.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  125:          blk.13.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  126:           blk.13.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  127:             blk.14.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  128:             blk.14.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  129:             blk.14.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  130:        blk.14.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  131:           blk.14.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  132:             blk.14.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  133:           blk.14.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  134:          blk.14.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  135:           blk.14.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  136:             blk.15.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  137:             blk.15.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  138:             blk.15.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  139:        blk.15.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  140:           blk.15.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  141:             blk.15.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  142:           blk.15.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  143:          blk.15.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  144:           blk.15.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  145:             blk.16.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  146:             blk.16.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  147:             blk.16.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  148:        blk.16.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  149:           blk.16.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  150:             blk.16.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  151:           blk.16.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  152:          blk.16.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  153:           blk.16.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  154:             blk.17.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  155:             blk.17.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  156:             blk.17.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  157:        blk.17.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  158:           blk.17.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  159:             blk.17.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  160:           blk.17.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  161:          blk.17.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  162:           blk.17.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  163:             blk.18.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  164:             blk.18.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  165:             blk.18.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  166:        blk.18.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  167:           blk.18.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  168:             blk.18.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  169:           blk.18.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  170:          blk.18.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  171:           blk.18.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  172:             blk.19.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  173:             blk.19.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  174:             blk.19.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  175:        blk.19.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  176:           blk.19.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  177:             blk.19.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  178:           blk.19.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  179:          blk.19.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  180:           blk.19.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  181:             blk.20.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  182:             blk.20.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  183:             blk.20.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  184:        blk.20.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  185:           blk.20.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  186:             blk.20.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  187:           blk.20.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  188:          blk.20.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  189:           blk.20.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  190:             blk.21.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  191:             blk.21.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  192:             blk.21.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  193:        blk.21.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  194:           blk.21.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  195:             blk.21.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  196:           blk.21.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  197:          blk.21.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  198:           blk.21.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  199:             blk.22.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  200:             blk.22.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  201:             blk.22.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  202:        blk.22.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  203:           blk.22.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  204:             blk.22.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  205:           blk.22.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  206:          blk.22.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  207:           blk.22.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  208:             blk.23.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  209:             blk.23.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  210:             blk.23.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  211:        blk.23.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  212:           blk.23.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  213:             blk.23.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  214:           blk.23.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  215:          blk.23.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  216:           blk.23.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  217:             blk.24.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  218:             blk.24.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  219:             blk.24.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  220:        blk.24.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  221:           blk.24.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  222:             blk.24.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  223:           blk.24.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  224:          blk.24.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  225:           blk.24.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  226:             blk.25.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  227:             blk.25.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  228:             blk.25.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  229:        blk.25.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  230:           blk.25.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  231:             blk.25.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  232:           blk.25.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  233:          blk.25.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  234:           blk.25.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  235:             blk.26.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  236:             blk.26.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  237:             blk.26.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  238:        blk.26.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  239:           blk.26.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  240:             blk.26.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  241:           blk.26.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  242:          blk.26.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  243:           blk.26.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  244:             blk.27.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  245:             blk.27.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  246:             blk.27.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  247:        blk.27.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  248:           blk.27.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  249:             blk.27.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  250:           blk.27.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  251:          blk.27.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  252:           blk.27.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  253:             blk.28.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  254:             blk.28.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  255:             blk.28.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  256:        blk.28.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  257:           blk.28.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  258:             blk.28.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  259:           blk.28.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  260:          blk.28.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  261:           blk.28.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  262:             blk.29.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  263:             blk.29.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  264:             blk.29.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  265:        blk.29.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  266:           blk.29.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  267:             blk.29.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  268:           blk.29.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  269:          blk.29.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  270:           blk.29.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  271:             blk.30.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  272:             blk.30.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  273:             blk.30.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  274:        blk.30.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  275:           blk.30.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  276:             blk.30.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  277:           blk.30.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  278:          blk.30.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  279:           blk.30.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  280:             blk.31.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  281:             blk.31.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  282:             blk.31.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  283:        blk.31.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  284:           blk.31.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  285:             blk.31.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  286:           blk.31.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  287:          blk.31.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  288:           blk.31.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  289:             blk.32.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  290:             blk.32.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  291:             blk.32.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  292:        blk.32.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  293:           blk.32.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  294:             blk.32.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  295:           blk.32.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  296:          blk.32.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  297:           blk.32.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  298:             blk.33.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  299:             blk.33.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  300:             blk.33.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  301:        blk.33.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  302:           blk.33.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  303:             blk.33.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  304:           blk.33.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  305:          blk.33.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  306:           blk.33.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  307:             blk.34.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  308:             blk.34.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  309:             blk.34.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  310:        blk.34.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  311:           blk.34.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  312:             blk.34.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  313:           blk.34.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  314:          blk.34.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  315:           blk.34.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  316:             blk.35.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  317:             blk.35.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  318:             blk.35.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  319:        blk.35.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  320:           blk.35.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  321:             blk.35.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  322:           blk.35.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  323:          blk.35.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  324:           blk.35.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  325:             blk.36.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  326:             blk.36.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  327:             blk.36.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  328:        blk.36.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  329:           blk.36.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  330:             blk.36.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  331:           blk.36.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  332:          blk.36.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  333:           blk.36.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  334:             blk.37.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  335:             blk.37.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  336:             blk.37.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  337:        blk.37.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  338:           blk.37.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  339:             blk.37.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  340:           blk.37.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  341:          blk.37.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  342:           blk.37.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  343:             blk.38.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  344:             blk.38.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  345:             blk.38.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  346:        blk.38.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  347:           blk.38.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  348:             blk.38.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  349:           blk.38.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  350:          blk.38.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  351:           blk.38.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  352:             blk.39.attn_q.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  353:             blk.39.attn_k.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  354:             blk.39.attn_v.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  355:        blk.39.attn_output.weight q5_1     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor  356:           blk.39.ffn_gate.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  357:             blk.39.ffn_up.weight q5_1     [  5120, 13696,     1,     1 ]
llama_model_loader: - tensor  358:           blk.39.ffn_down.weight q5_1     [ 13696,  5120,     1,     1 ]
llama_model_loader: - tensor  359:          blk.39.attn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  360:           blk.39.ffn_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  361:               output_norm.weight f32      [  5120,     1,     1,     1 ]
llama_model_loader: - tensor  362:                    output.weight q6_K     [  5120, 152064,     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.merges arr     
llama_model_loader: - kv  17:                tokenizer.ggml.bos_token_id u32     
llama_model_loader: - kv  18:                tokenizer.ggml.eos_token_id u32     
llama_model_loader: - kv  19:            tokenizer.ggml.padding_token_id u32     
llama_model_loader: - kv  20:               general.quantization_version u32     
llama_model_loader: - type  f32:   81 tensors
llama_model_loader: - type q5_1:  281 tensors
llama_model_loader: - type q6_K:    1 tensors
llm_load_vocab: mismatch in special tokens definition ( 421/152064 vs 213/152064 ).
llm_load_print_meta: format           = unknown
llm_load_print_meta: arch             = llama
llm_load_print_meta: vocab type       = BPE
llm_load_print_meta: n_vocab          = 152064
llm_load_print_meta: n_merges         = 109170
llm_load_print_meta: n_ctx_train      = 8192
llm_load_print_meta: n_embd           = 5120
llm_load_print_meta: n_head           = 40
llm_load_print_meta: n_head_kv        = 40
llm_load_print_meta: n_layer          = 40
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-06
llm_load_print_meta: f_clamp_kqv      = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: n_ff             = 13696
llm_load_print_meta: freq_base_train  = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: model type       = 13B
llm_load_print_meta: model ftype      = mostly Q5_1
llm_load_print_meta: model params     = 14.17 B
llm_load_print_meta: model size       = 9.95 GiB (6.03 BPW) 
llm_load_print_meta: general.name   = causallm_14b
llm_load_print_meta: BOS token = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token = 151643 '<|endoftext|>'
llm_load_print_meta: PAD token = 151643 '<|endoftext|>'
llm_load_print_meta: LF token  = 128 'Ä'
llm_load_tensors: ggml ctx size =    0.12 MB
llm_load_tensors: using CUDA for GPU acceleration
llm_load_tensors: mem required  =  557.00 MB
llm_load_tensors: offloading 40 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 43/43 layers to GPU
llm_load_tensors: VRAM used: 9629.41 MB
...........................................................................................
llama_new_context_with_model: n_ctx      = 512
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 = 400.00 MB
llama_new_context_with_model: kv self size  =  400.00 MB
llama_new_context_with_model: compute buffer total size = 313.13 MB
llama_new_context_with_model: VRAM scratch buffer: 307.00 MB
llama_new_context_with_model: total VRAM used: 10336.41 MB (model: 9629.41 MB, context: 707.00 MB)

system_info: n_threads = 12 / 24 | AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | 
main: interactive mode on.
sampling: 
        repeat_last_n = 64, repeat_penalty = 1.100, frequency_penalty = 0.000, presence_penalty = 0.000
        top_k = 40, tfs_z = 1.000, top_p = 0.950, typical_p = 1.000, temp = 0.800
        mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
generate: n_ctx = 512, n_batch = 512, n_predict = -1, n_keep = 0


== Running in interactive mode. ==
 - Press Ctrl+C to interject at any time.
 - Press Return to return control to LLaMa.
 - To return control without starting a new line, end your input with '/'.
 - If you want to submit another line, end your input with '\'.

<|endoftext|>

你好
CUDA error 9 at ggml-cuda.cu:6862: invalid configuration argument
current device: 0

[JeremyBickel]

I'm getting an error from the same line of code, but mine says "no kernel image is available for execution on the device", instead of "invalid configuration argument".
SciSharp/LLamaSharp#189

[RoacherM]

same error
llm_load_vocab: mismatch in special tokens definition ( 9/100008 vs 8/100008 ).
llm_load_print_meta: format = unknown
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 100008
llm_load_print_meta: n_merges = 99743
llm_load_print_meta: n_ctx_train = 4096
llm_load_print_meta: n_embd = 6144
llm_load_print_meta: n_head = 48
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_layer = 60
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_gqa = 6
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 = 24576
llm_load_print_meta: freq_base_train = 10000.0
llm_load_print_meta: freq_scale_train = 0.25
llm_load_print_meta: model type = 30B
llm_load_print_meta: model ftype = mostly Q4_K - Medium
llm_load_print_meta: model params = 33.69 B
llm_load_print_meta: model size = 18.93 GiB (4.83 BPW)
llm_load_print_meta: general.name = LLaMA v2
llm_load_print_meta: BOS token = 0 '<|endoftext|>'
llm_load_print_meta: EOS token = 0 '<|endoftext|>'
llm_load_print_meta: UNK token = 0 '<|endoftext|>'
llm_load_print_meta: LF token = 129 'Ä'
llm_load_tensors: ggml ctx size = 0.18 MB
llm_load_tensors: using CUDA for GPU acceleration
llm_load_tensors: mem required = 13118.48 MB
llm_load_tensors: offloading 20 repeating layers to GPU
llm_load_tensors: offloaded 20/63 layers to GPU
llm_load_tensors: VRAM used: 6270.00 MB
..................................................................................................
llama_new_context_with_model: n_ctx = 512
llama_new_context_with_model: freq_base = 10000.0
llama_new_context_with_model: freq_scale = 0.25
llama_new_context_with_model: kv self size = 120.00 MB
llama_new_context_with_model: compute buffer total size = 213.45 MB
llama_new_context_with_model: VRAM scratch buffer: 207.33 MB
llama_new_context_with_model: total VRAM used: 6477.33 MB (model: 6270.00 MB, context: 207.33 MB)

system_info: n_threads = 16 / 32 | AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 |
main: interactive mode on.
Reverse prompt: 'User:'
sampling: repeat_last_n = 64, repeat_penalty = 1.000000, presence_penalty = 0.000000, frequency_penalty = 0.000000, top_k = 40, tfs_z = 1.000000, top_p = 0.950000, typical_p = 1.000000, temp = 0.800000, mirostat = 0, mirostat_lr = 0.100000, mirostat_ent = 5.000000
generate: n_ctx = 512, n_batch = 512, n_predict = 512, n_keep = 0

== Running in interactive mode. ==

• Press Ctrl+C to interject at any time.
• Press Return to return control to LLaMa.
• To return control without starting a new line, end your input with '/'.
• If you want to submit another line, end your input with ''.

Transcript of a dialog, where the User interacts with an Assistant named Bob. Bob is helpful, kind, honest, good at writing, and never fails to answer the User's requests immediately and with precision.

User: Hello, Bob.
Bob: Hello. How may I help you today?
User: Please tell me the largest city in Europe.
Bob: Sure. The largest city in Europe is Moscow, the capital of Russia.
User:你好
Bob
CUDA error 9 at ggml-cuda.cu:6862: invalid configuration argument
current device: 0

[slaren]

A call stack and the kernel launch parameters that cause this error would help get this fixed quicker.

[happyme531]

A call stack and the kernel launch parameters that cause this error would help get this fixed quicker.

Here it is.

== Running in interactive mode. ==
 - Press Ctrl+C to interject at any time.
 - Press Return to return control to LLaMa.
 - To return control without starting a new line, end your input with '/'.
 - If you want to submit another line, end your input with '\'.

<|endoftext|>
warning: Cuda API error detected: cudaLaunchKernel returned (0x9)

warning: Cuda API error detected: cudaGetLastError returned (0x9)


Thread 1 "main" hit Breakpoint 1, ggml_cuda_op_mul_mat (src0=0x7fff9ba002e0, src1=0x7ff99e918dc0, dst=0x7ff99e918f20, op=0x5555556bcb9b <ggml_cuda_op_mul_mat_vec_q(ggml_tensor const*, ggml_tensor const*, ggml_tensor*, char const*, float const*, char const*, float*, long, long, long, long, CUstream_st* const&)>, convert_src1_to_q8_1=true) at /mnt/ntfs/llm/llama.cpp/ggml-cuda.cu:6863
6863                        printf("Error in mul_mat\n");}
(cuda-gdb) bt
#0  ggml_cuda_op_mul_mat (src0=0x7fff9ba002e0, src1=0x7ff99e918dc0, dst=0x7ff99e918f20, 
    op=0x5555556bcb9b <ggml_cuda_op_mul_mat_vec_q(ggml_tensor const*, ggml_tensor const*, ggml_tensor*, char const*, float const*, char const*, float*, long, long, long, long, CUstream_st* const&)>, convert_src1_to_q8_1=true)
    at /mnt/ntfs/llm/llama.cpp/ggml-cuda.cu:6863
#1  0x00005555556a7c87 in ggml_cuda_mul_mat (src0=0x7fff9ba002e0, src1=0x7ff99e918dc0, dst=0x7ff99e918f20) at /mnt/ntfs/llm/llama.cpp/ggml-cuda.cu:7077
#2  0x00005555556a9fad in ggml_cuda_compute_forward (params=0x7ffffffead10, tensor=0x7ff99e918f20) at /mnt/ntfs/llm/llama.cpp/ggml-cuda.cu:7550
#3  0x00005555555a901a in ggml_compute_forward (params=0x7ffffffead10, tensor=0x7ff99e918f20) at ggml.c:16606
#4  0x00005555555ae0eb in ggml_graph_compute_thread (data=0x7ffffffead60) at ggml.c:18327
#5  0x00005555555af9b0 in ggml_graph_compute (cgraph=0x7ff99e800020, cplan=0x7ffffffeae60) at ggml.c:18903
#6  0x00005555555bd5a4 in ggml_graph_compute_helper (buf=..., graph=0x7ff99e800020, n_threads=1) at llama.cpp:568
#7  0x00005555555dea55 in llama_decode_internal (lctx=..., batch=...) at llama.cpp:6006
#8  0x00005555555ebcd3 in llama_decode (ctx=0x555556e3a4a0, batch=...) at llama.cpp:9656
#9  0x000055555556696f in main (argc=6, argv=0x7fffffffce58) at examples/main/main.cpp:584
(cuda-gdb) info cuda kernels
No CUDA kernels.
(cuda-gdb) info locals
i02 = 0
src1_ddq_i_offset = 0
src0_dd_i = 0x7ff9c8000000 ""
src1_ddf_i = 0x7ff96a000000
dst_dd_i = 0x7ff97d600000
i03 = 0
src1_ddq_i = 0x7fff9b9bfc00 ""
i0 = 0
src1_on_device = true
dst_on_device = false
row_diff = 152064
stream = 0x555556578a70
id = 0
is = 0
src1_ncols = 1
src1_col_0 = 0
ne00 = 5120
ne01 = 152064
ne02 = 1
ne03 = 1
nrows0 = 152064
ne10 = 5120
ne11 = 1
ne12 = 1
ne13 = 1
nrows1 = 1
ne0 = 152064
ne1 = 1
nb2 = 608256
nb3 = 608256
i02_divisor = 1
src0_ts = 210
src0_bs = 256
q8_1_ts = 36
q8_1_bs = 32
src0_extra = 0x55555b576660
src1_extra = 0x7fffbc91f390
dst_extra = 0x0
src0_on_device = true
src0_is_contiguous = true
src1_is_contiguous = true
src1_padded_col_size = 5120
split = true
src0_dd = {0x7ff9c8000000 "", 0x0 <repeats 15 times>}
src1_ddf = {0x7ff96a000000, 0x0 <repeats 15 times>}
src1_ddq = {0x7fff9b9bfc00 "", 0x0 <repeats 15 times>}
dst_dd = {0x7ff97d600000, 0x0 <repeats 15 times>}
src0_as = {0 <repeats 16 times>}
src1_asf = {0 <repeats 16 times>}
src1_asq = {17408, 0 <repeats 15 times>}
dst_as = {5504256, 0 <repeats 15 times>}
--Type <RET> for more, q to quit, c to continue without paging--
row_low = {0, 0, 93825000467376, 0, 4294967306, 140710083923392, 140735804342656, 140737239086272, 5120, 1, 93825093053984, 93825093053984, 140737488268256, 93825028256304, 0, 93824993610497}
row_high = {152064, 140710083923392, 140735804342656, 140710083923040, 128, 282578800082984, 4, 512, 512, 0, 0, 0, 93825009158768, 140709201969152, 140735804015616, 140709201969152}
src1_col_stride = 1

[slaren]

The problem here seems to be that n_vocab is very large, and this value is used as the y dimension of the block size, which has a maximum of 65535. The correct fix would be to move this to the x dimension, which has no such limit. As a workaround, building with a higher value of LLAMA_CUDA_MMV_Y may fix this, try adding LLAMA_CUDA_MMV_Y=4 to the make or cmake command line, since this acts as a divisor of the block size.

[ArtyomZemlyak]

@slaren this also worked with CausalLM on GPU! (earlier have same issue)

[wzp123123]

I test baichuan2, it works well On GPU, thanks a lot! @slaren

[slaren]

We still need to fix though, this is just a workaround.

[zolastro]

Not sure if I made something wrong, but after recompiling with the LLAMA_CUDA_MMV_Y=4 flag and correctly loading the Bloom model on GPU, it actually runs very slow compared to other models. I have made some test compared with Falcon7b and LLama v2 and it runs x30 times slower in GPU using q8_0 quantization. Is this something expected given this workaround?