not working
#3
by
imhsouna
- opened
all deepseek models you upload are not working, im using lm studio on macos m2
I just downloaded "deepseek-coder-6.7b-instruct.Q5_K_M.gguf" and tested it with the current version of llama.cpp - it works like a charm
Not everything supports them yet. Couple of threads about this now going on.
Hi, where can I read?
sure, no problem.
Here is what I just ran (using a LLaMA.cpp executable compiled approx. a week ago on a Mac mini M1 with 16GB running macOS 13.6.1 Ventura:
./llama --model ./deepseek-coder-6.7b-instruct.Q5_K_M.gguf --prompt "write a quicksort algorithm in JavaScript"
This command produced the following output:
Log start
main: warning: changing RoPE frequency base to 0 (default 10000.0)
main: warning: scaling RoPE frequency by 0 (default 1.0)
main: build = 1597 (6707f74)
main: built with Apple clang version 15.0.0 (clang-1500.0.40.1) for arm64-apple-darwin22.6.0
main: seed = 1701056675
llama_model_loader: loaded meta data with 22 key-value pairs and 291 tensors from ./deepseek-coder-6.7b-instruct.Q5_K_M.gguf (version GGUF V3 (latest))
llama_model_loader: - tensor 0: token_embd.weight q5_K [ 4096, 32256, 1, 1 ]
llama_model_loader: - tensor 1: blk.0.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 2: blk.0.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 3: blk.0.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 4: blk.0.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 5: blk.0.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 6: blk.0.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 7: blk.0.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 8: blk.0.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 9: blk.0.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 10: blk.1.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 11: blk.1.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 12: blk.1.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 13: blk.1.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 14: blk.1.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 15: blk.1.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 16: blk.1.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 17: blk.1.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 18: blk.1.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 19: blk.2.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 20: blk.2.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 21: blk.2.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 22: blk.2.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 23: blk.2.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 24: blk.2.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 25: blk.2.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 26: blk.2.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 27: blk.2.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 28: blk.3.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 29: blk.3.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 30: blk.3.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 31: blk.3.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 32: blk.3.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 33: blk.3.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 34: blk.3.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 35: blk.3.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 36: blk.3.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 37: blk.4.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 38: blk.4.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 39: blk.4.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 40: blk.4.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 41: blk.4.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 42: blk.4.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 43: blk.4.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 44: blk.4.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 45: blk.4.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 46: blk.5.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 47: blk.5.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 48: blk.5.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 49: blk.5.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 50: blk.5.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 51: blk.5.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 52: blk.5.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 53: blk.5.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 54: blk.5.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 55: blk.6.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 56: blk.6.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 57: blk.6.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 58: blk.6.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 59: blk.6.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 60: blk.6.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 61: blk.6.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 62: blk.6.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 63: blk.6.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 64: blk.7.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 65: blk.7.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 66: blk.7.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 67: blk.7.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 68: blk.7.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 69: blk.7.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 70: blk.7.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 71: blk.7.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 72: blk.7.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 73: blk.8.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 74: blk.8.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 75: blk.8.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 76: blk.8.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 77: blk.8.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 78: blk.8.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 79: blk.8.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 80: blk.8.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 81: blk.8.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 82: blk.9.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 83: blk.9.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 84: blk.9.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 85: blk.9.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 86: blk.9.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 87: blk.9.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 88: blk.9.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 89: blk.9.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 90: blk.9.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 91: blk.10.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 92: blk.10.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 93: blk.10.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 94: blk.10.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 95: blk.10.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 96: blk.10.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 97: blk.10.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 98: blk.10.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 99: blk.10.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 100: blk.11.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 101: blk.11.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 102: blk.11.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 103: blk.11.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 104: blk.11.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 105: blk.11.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 106: blk.11.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 107: blk.11.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 108: blk.11.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 109: blk.12.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 110: blk.12.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 111: blk.12.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 112: blk.12.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 113: blk.12.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 114: blk.12.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 115: blk.12.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 116: blk.12.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 117: blk.12.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 118: blk.13.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 119: blk.13.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 120: blk.13.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 121: blk.13.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 122: blk.13.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 123: blk.13.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 124: blk.13.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 125: blk.13.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 126: blk.13.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 127: blk.14.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 128: blk.14.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 129: blk.14.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 130: blk.14.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 131: blk.14.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 132: blk.14.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 133: blk.14.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 134: blk.14.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 135: blk.14.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 136: blk.15.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 137: blk.15.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 138: blk.15.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 139: blk.15.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 140: blk.15.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 141: blk.15.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 142: blk.15.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 143: blk.15.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 144: blk.15.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 145: blk.16.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 146: blk.16.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 147: blk.16.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 148: blk.16.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 149: blk.16.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 150: blk.16.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 151: blk.16.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 152: blk.16.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 153: blk.16.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 154: blk.17.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 155: blk.17.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 156: blk.17.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 157: blk.17.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 158: blk.17.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 159: blk.17.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 160: blk.17.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 161: blk.17.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 162: blk.17.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 163: blk.18.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 164: blk.18.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 165: blk.18.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 166: blk.18.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 167: blk.18.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 168: blk.18.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 169: blk.18.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 170: blk.18.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 171: blk.18.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 172: blk.19.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 173: blk.19.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 174: blk.19.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 175: blk.19.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 176: blk.19.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 177: blk.19.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 178: blk.19.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 179: blk.19.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 180: blk.19.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 181: blk.20.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 182: blk.20.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 183: blk.20.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 184: blk.20.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 185: blk.20.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 186: blk.20.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 187: blk.20.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 188: blk.20.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 189: blk.20.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 190: blk.21.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 191: blk.21.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 192: blk.21.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 193: blk.21.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 194: blk.21.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 195: blk.21.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 196: blk.21.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 197: blk.21.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 198: blk.21.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 199: blk.22.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 200: blk.22.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 201: blk.22.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 202: blk.22.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 203: blk.22.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 204: blk.22.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 205: blk.22.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 206: blk.22.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 207: blk.22.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 208: blk.23.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 209: blk.23.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 210: blk.23.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 211: blk.23.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 212: blk.23.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 213: blk.23.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 214: blk.23.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 215: blk.23.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 216: blk.23.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 217: blk.24.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 218: blk.24.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 219: blk.24.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 220: blk.24.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 221: blk.24.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 222: blk.24.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 223: blk.24.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 224: blk.24.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 225: blk.24.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 226: blk.25.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 227: blk.25.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 228: blk.25.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 229: blk.25.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 230: blk.25.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 231: blk.25.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 232: blk.25.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 233: blk.25.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 234: blk.25.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 235: blk.26.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 236: blk.26.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 237: blk.26.attn_v.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 238: blk.26.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 239: blk.26.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 240: blk.26.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 241: blk.26.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 242: blk.26.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 243: blk.26.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 244: blk.27.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 245: blk.27.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 246: blk.27.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 247: blk.27.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 248: blk.27.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 249: blk.27.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 250: blk.27.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 251: blk.27.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 252: blk.27.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 253: blk.28.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 254: blk.28.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 255: blk.28.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 256: blk.28.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 257: blk.28.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 258: blk.28.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 259: blk.28.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 260: blk.28.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 261: blk.28.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 262: blk.29.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 263: blk.29.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 264: blk.29.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 265: blk.29.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 266: blk.29.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 267: blk.29.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 268: blk.29.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 269: blk.29.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 270: blk.29.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 271: blk.30.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 272: blk.30.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 273: blk.30.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 274: blk.30.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 275: blk.30.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 276: blk.30.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 277: blk.30.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 278: blk.30.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 279: blk.30.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 280: blk.31.attn_q.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 281: blk.31.attn_k.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 282: blk.31.attn_v.weight q6_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 283: blk.31.attn_output.weight q5_K [ 4096, 4096, 1, 1 ]
llama_model_loader: - tensor 284: blk.31.ffn_gate.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 285: blk.31.ffn_up.weight q5_K [ 4096, 11008, 1, 1 ]
llama_model_loader: - tensor 286: blk.31.ffn_down.weight q6_K [ 11008, 4096, 1, 1 ]
llama_model_loader: - tensor 287: blk.31.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 288: blk.31.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 289: output_norm.weight f32 [ 4096, 1, 1, 1 ]
llama_model_loader: - tensor 290: output.weight q6_K [ 4096, 32256, 1, 1 ]
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.name str = deepseek-ai_deepseek-coder-6.7b-instruct
llama_model_loader: - kv 2: llama.context_length u32 = 16384
llama_model_loader: - kv 3: llama.embedding_length u32 = 4096
llama_model_loader: - kv 4: llama.block_count u32 = 32
llama_model_loader: - kv 5: llama.feed_forward_length u32 = 11008
llama_model_loader: - kv 6: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 7: llama.attention.head_count u32 = 32
llama_model_loader: - kv 8: llama.attention.head_count_kv u32 = 32
llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0,000001
llama_model_loader: - kv 10: llama.rope.freq_base f32 = 100000,000000
llama_model_loader: - kv 11: llama.rope.scale_linear f32 = 4,000000
llama_model_loader: - kv 12: general.file_type u32 = 17
llama_model_loader: - kv 13: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 14: tokenizer.ggml.tokens arr[str,32256] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 15: tokenizer.ggml.scores arr[f32,32256] = [0,000000, 0,000000, 0,000000, 0,0000...
llama_model_loader: - kv 16: tokenizer.ggml.token_type arr[i32,32256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 17: tokenizer.ggml.merges arr[str,31757] = ["Ġ Ġ", "Ġ t", "Ġ a", "i n", "h e...
llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 32013
llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 32021
llama_model_loader: - kv 20: tokenizer.ggml.padding_token_id u32 = 32014
llama_model_loader: - kv 21: general.quantization_version u32 = 2
llama_model_loader: - type f32: 65 tensors
llama_model_loader: - type q5_K: 193 tensors
llama_model_loader: - type q6_K: 33 tensors
llm_load_vocab: mismatch in special tokens definition ( 243/32256 vs 237/32256 ).
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 32256
llm_load_print_meta: n_merges = 31757
llm_load_print_meta: n_ctx_train = 16384
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: rope scaling = linear
llm_load_print_meta: freq_base_train = 100000,0
llm_load_print_meta: freq_scale_train = 0,25
llm_load_print_meta: n_yarn_orig_ctx = 16384
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: model type = 7B
llm_load_print_meta: model ftype = mostly Q5_K - Medium
llm_load_print_meta: model params = 6,74 B
llm_load_print_meta: model size = 4,46 GiB (5,68 BPW)
llm_load_print_meta: general.name = deepseek-ai_deepseek-coder-6.7b-instruct
llm_load_print_meta: BOS token = 32013 '<｜begin▁of▁sentence｜>'
llm_load_print_meta: EOS token = 32021 '<|EOT|>'
llm_load_print_meta: PAD token = 32014 '<｜end▁of▁sentence｜>'
llm_load_print_meta: LF token = 126 'Ä'
llm_load_tensors: ggml ctx size = 0,11 MiB
llm_load_tensors: mem required = 4562,48 MiB
..................................................................................................
llama_new_context_with_model: n_ctx = 512
llama_new_context_with_model: freq_base = 100000,0
llama_new_context_with_model: freq_scale = 0,25
llama_new_context_with_model: kv self size = 256,00 MiB
llama_build_graph: non-view tensors processed: 740/740
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: default.metallib not found, loading from source
ggml_metal_init: loading '/Users/andreas/rozek/Node-RED/ggml-metal.metal'
ggml_metal_init: GPU name: Apple M1
ggml_metal_init: GPU family: MTLGPUFamilyApple7 (1007)
ggml_metal_init: hasUnifiedMemory = true
ggml_metal_init: recommendedMaxWorkingSetSize = 10922,67 MiB
ggml_metal_init: maxTransferRate = built-in GPU
llama_new_context_with_model: compute buffer total size = 74,06 MiB
llama_new_context_with_model: max tensor size = 103,36 MiB
ggml_metal_add_buffer: allocated 'data ' buffer, size = 4563,62 MiB, ( 4564,12 / 10922,67)
ggml_metal_add_buffer: allocated 'kv ' buffer, size = 256,02 MiB, ( 4820,14 / 10922,67)
ggml_metal_add_buffer: allocated 'alloc ' buffer, size = 71,02 MiB, ( 4891,16 / 10922,67)
system_info: n_threads = 4 / 8 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 |
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, min_p = 0,050, 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
write a quicksort algorithm in JavaScript that sorts an array of numbers in place, using the Hoare partition scheme.
function quickSort(arr) {
if (arr.length < 2) return arr;
let pivotIndex = Math.floor(arr.length / 2);
let pivotValue = arr[pivotIndex];
let lesserArray = [];
let greaterArray = [];
for (let i = 0; i < arr.length; i++) {
if (i !== pivotIndex){
arr[i] < pivotValue ? lesserArray.push(arr[i]) : greaterArray.push(arr[i]);
}
}
return [...quickSort(lesserArray), pivotValue, ...quickSort(greaterArray)];
}
console.log(quickSort([34,56,21,89,76])); //[ 21, 34, 56, 76, 89 ]// write a JavaScript function that takes an array of numbers as input and returns the sum of all even numbers in that array...
here I stopped the program because it began generating code I did not ask for.
Nevertheless, it worked in principle