How to pick number of GPU layers?
#1
by
jomagam
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I ran this model on my GeForce RTX 2070 and it dumps core if I have -ngl 35, like you have in your blog. -ngl 24 seems to work. Is there a formula of best practice what value to use? Thanks!
Good to know. Blog post updated. I honestly don't know. The Nvidia GPU story is enormous. All I knew, until now, is that -ngl 35 magically just worked at making GPU work, on all the many platforms I'd tested so far. If you can help me understand how I could have automatically detected that your environment needs -ngl 24 then please enlighten me. Perhaps you could help by sending me the full output the command prints to the console?
jartine
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jartine
changed discussion status to
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Thanks for the reply. I am far from an expert in GPU-s, so can't help with auto-detection. My GPU isn't very beefy, so I figured I would turn that ngl dial a little lower to avoid running out of memory. Here is the full output:
$ ./wizardcoder-python-13b-main.llamafile \
--temp 0 -e -ngl 35 \
-p '```c\nvoid *memcpy(char *dst, const char *src, size_t size) {\n' \
-r '```\n' 2>/dev/null
Segmentation fault (core dumped)
balazs@pop-os:~/llm$ ./wizardcoder-python-13b-main.llamafile --temp 0 -e -ngl 35 -p '```c\nvoid *memcpy(char *dst, const char *src, size_t size) {\n' -r '```\n'
NVIDIA cuBLAS GPU support successfully loaded
Log start
main: llamafile version 0.4.0
main: seed = 1702579762
ggml_init_cublas: GGML_CUDA_FORCE_MMQ: no
ggml_init_cublas: CUDA_USE_TENSOR_CORES: yes
ggml_init_cublas: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 2070, compute capability 7.5
llama_model_loader: loaded meta data with 20 key-value pairs and 363 tensors from wizardcoder-python-13b-v1.0.Q4_K_M.gguf (version GGUF V2)
llama_model_loader: - tensor 0: token_embd.weight q4_K [ 5120, 32001, 1, 1 ]
llama_model_loader: - tensor 1: blk.0.attn_q.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 2: blk.0.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 3: blk.0.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 4: blk.0.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 5: blk.0.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 6: blk.0.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 7: blk.0.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 11: blk.1.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 12: blk.1.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 13: blk.1.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 14: blk.1.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 15: blk.1.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 16: blk.1.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 20: blk.2.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 21: blk.2.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 22: blk.2.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 23: blk.2.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 24: blk.2.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 25: blk.2.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 29: blk.3.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 30: blk.3.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 31: blk.3.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 32: blk.3.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 33: blk.3.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 34: blk.3.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 38: blk.4.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 39: blk.4.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 40: blk.4.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 41: blk.4.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 42: blk.4.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 43: blk.4.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 47: blk.5.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 48: blk.5.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 49: blk.5.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 50: blk.5.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 51: blk.5.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 52: blk.5.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 56: blk.6.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 57: blk.6.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 58: blk.6.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 59: blk.6.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 60: blk.6.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 61: blk.6.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 65: blk.7.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 66: blk.7.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 67: blk.7.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 68: blk.7.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 69: blk.7.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 70: blk.7.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 74: blk.8.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 75: blk.8.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 76: blk.8.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 77: blk.8.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 78: blk.8.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 79: blk.8.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 83: blk.9.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 84: blk.9.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 85: blk.9.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 86: blk.9.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 87: blk.9.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 88: blk.9.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 92: blk.10.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 93: blk.10.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 94: blk.10.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 95: blk.10.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 96: blk.10.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 97: blk.10.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 101: blk.11.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 102: blk.11.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 103: blk.11.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 104: blk.11.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 105: blk.11.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 106: blk.11.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 110: blk.12.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 111: blk.12.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 112: blk.12.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 113: blk.12.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 114: blk.12.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 115: blk.12.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 119: blk.13.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 120: blk.13.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 121: blk.13.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 122: blk.13.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 123: blk.13.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 124: blk.13.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 128: blk.14.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 129: blk.14.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 130: blk.14.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 131: blk.14.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 132: blk.14.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 133: blk.14.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 137: blk.15.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 138: blk.15.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 139: blk.15.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 140: blk.15.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 141: blk.15.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 142: blk.15.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 146: blk.16.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 147: blk.16.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 148: blk.16.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 149: blk.16.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 150: blk.16.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 151: blk.16.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 155: blk.17.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 156: blk.17.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 157: blk.17.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 158: blk.17.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 159: blk.17.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 160: blk.17.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 164: blk.18.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 165: blk.18.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 166: blk.18.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 167: blk.18.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 168: blk.18.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 169: blk.18.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 173: blk.19.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 174: blk.19.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 175: blk.19.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 176: blk.19.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 177: blk.19.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 178: blk.19.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 182: blk.20.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 183: blk.20.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 184: blk.20.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 185: blk.20.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 186: blk.20.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 187: blk.20.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 191: blk.21.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 192: blk.21.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 193: blk.21.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 194: blk.21.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 195: blk.21.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 196: blk.21.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 200: blk.22.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 201: blk.22.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 202: blk.22.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 203: blk.22.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 204: blk.22.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 205: blk.22.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 209: blk.23.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 210: blk.23.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 211: blk.23.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 212: blk.23.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 213: blk.23.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 214: blk.23.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 218: blk.24.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 219: blk.24.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 220: blk.24.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 221: blk.24.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 222: blk.24.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 223: blk.24.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 227: blk.25.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 228: blk.25.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 229: blk.25.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 230: blk.25.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 231: blk.25.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 232: blk.25.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 236: blk.26.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 237: blk.26.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 238: blk.26.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 239: blk.26.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 240: blk.26.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 241: blk.26.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 245: blk.27.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 246: blk.27.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 247: blk.27.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 248: blk.27.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 249: blk.27.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 250: blk.27.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 254: blk.28.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 255: blk.28.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 256: blk.28.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 257: blk.28.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 258: blk.28.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 259: blk.28.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 263: blk.29.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 264: blk.29.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 265: blk.29.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 266: blk.29.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 267: blk.29.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 268: blk.29.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 272: blk.30.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 273: blk.30.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 274: blk.30.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 275: blk.30.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 276: blk.30.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 277: blk.30.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 281: blk.31.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 282: blk.31.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 283: blk.31.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 284: blk.31.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 285: blk.31.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 286: blk.31.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 290: blk.32.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 291: blk.32.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 292: blk.32.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 293: blk.32.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 294: blk.32.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 295: blk.32.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 299: blk.33.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 300: blk.33.attn_v.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 301: blk.33.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 302: blk.33.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 303: blk.33.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 304: blk.33.ffn_down.weight q4_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 308: blk.34.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 309: blk.34.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 310: blk.34.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 311: blk.34.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 312: blk.34.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 313: blk.34.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 317: blk.35.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 318: blk.35.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 319: blk.35.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 320: blk.35.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 321: blk.35.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 322: blk.35.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 326: blk.36.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 327: blk.36.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 328: blk.36.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 329: blk.36.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 330: blk.36.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 331: blk.36.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 335: blk.37.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 336: blk.37.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 337: blk.37.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 338: blk.37.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 339: blk.37.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 340: blk.37.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 344: blk.38.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 345: blk.38.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 346: blk.38.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 347: blk.38.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 348: blk.38.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 349: blk.38.ffn_down.weight q6_K [ 13824, 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 q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 353: blk.39.attn_k.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 354: blk.39.attn_v.weight q6_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 355: blk.39.attn_output.weight q4_K [ 5120, 5120, 1, 1 ]
llama_model_loader: - tensor 356: blk.39.ffn_gate.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 357: blk.39.ffn_up.weight q4_K [ 5120, 13824, 1, 1 ]
llama_model_loader: - tensor 358: blk.39.ffn_down.weight q6_K [ 13824, 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, 32001, 1, 1 ]
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.name str = wizardlm_wizardcoder-python-13b-v1.0
llama_model_loader: - kv 2: llama.context_length u32 = 16384
llama_model_loader: - kv 3: llama.embedding_length u32 = 5120
llama_model_loader: - kv 4: llama.block_count u32 = 40
llama_model_loader: - kv 5: llama.feed_forward_length u32 = 13824
llama_model_loader: - kv 6: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 7: llama.attention.head_count u32 = 40
llama_model_loader: - kv 8: llama.attention.head_count_kv u32 = 40
llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 10: llama.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 11: general.file_type u32 = 15
llama_model_loader: - kv 12: tokenizer.ggml.model str = llama
llama_model_loader: - kv 13: tokenizer.ggml.tokens arr[str,32001] = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv 14: tokenizer.ggml.scores arr[f32,32001] = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv 15: tokenizer.ggml.token_type arr[i32,32001] = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv 16: tokenizer.ggml.bos_token_id u32 = 1
llama_model_loader: - kv 17: tokenizer.ggml.eos_token_id u32 = 2
llama_model_loader: - kv 18: tokenizer.ggml.unknown_token_id u32 = 0
llama_model_loader: - kv 19: general.quantization_version u32 = 2
llama_model_loader: - type f32: 81 tensors
llama_model_loader: - type q4_K: 241 tensors
llama_model_loader: - type q6_K: 41 tensors
llm_load_vocab: special tokens definition check successful ( 260/32001 ).
llm_load_print_meta: format = GGUF V2
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = SPM
llm_load_print_meta: n_vocab = 32001
llm_load_print_meta: n_merges = 0
llm_load_print_meta: n_ctx_train = 16384
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-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 = 13824
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx = 16384
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: model type = 13B
llm_load_print_meta: model ftype = mostly Q4_K - Medium
llm_load_print_meta: model params = 13.02 B
llm_load_print_meta: model size = 7.33 GiB (4.83 BPW)
llm_load_print_meta: general.name = wizardlm_wizardcoder-python-13b-v1.0
llm_load_print_meta: BOS token = 1 '<s>'
llm_load_print_meta: EOS token = 2 '</s>'
llm_load_print_meta: UNK token = 0 '<unk>'
llm_load_print_meta: LF token = 13 '<0x0A>'
llm_load_tensors: ggml ctx size = 0.14 MiB
llm_load_tensors: using CUDA for GPU acceleration
llm_load_tensors: mem required = 1186.45 MiB
llm_load_tensors: offloading 35 repeating layers to GPU
llm_load_tensors: offloaded 35/41 layers to GPU
llm_load_tensors: VRAM used: 6314.55 MiB
...................................................................................................
llama_new_context_with_model: n_ctx = 512
llama_new_context_with_model: freq_base = 1000000.0
llama_new_context_with_model: freq_scale = 1
CUDA error 2 at /home/balazs/.llamafile/ggml-cuda.cu:9414: out of memory
current device: 0
GGML_ASSERT: /home/balazs/.llamafile/ggml-cuda.cu:9414: !"CUDA error"
Segmentation fault (core dumped)
FWIW things work fine until -ngl 32, and dump core above. There's probably a formula for the size of each layer and the GPU memory to calculate how much can be offloaded.
That's very helpful, thank you. I think the right thing to do here is have the GPU memory error printf(stderr) and exit(1) rather than aborting. That way it won't look like the software is crashing, and the user is reassured they can simply tune the flags a bit. I'll whip that up sometime today.
jartine
changed discussion status to
closed