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Created October 3, 2023 15:45
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Log start
main: build = 1311 (ff5a3f0)
main: built with Apple clang version 15.0.0 (clang-1500.0.40.1) for x86_64-apple-darwin22.6.0
main: seed = 42
llama_model_loader: loaded meta data with 20 key-value pairs and 201 tensors from /Users/alleon_g/.cache/llama.cpp/models/TinyLlama-1.1B-Chat-v0.3.Q5_K.gguf (version GGUF V2 (latest))
llama_model_loader: - tensor 0: token_embd.weight q5_K [ 2048, 32003, 1, 1 ]
llama_model_loader: - tensor 1: blk.0.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 2: blk.0.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 3: blk.0.attn_v.weight q6_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 4: blk.0.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 5: blk.0.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 6: blk.0.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 7: blk.0.ffn_down.weight q6_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 8: blk.0.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 9: blk.0.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 10: blk.1.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 11: blk.1.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 12: blk.1.attn_v.weight q6_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 13: blk.1.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 14: blk.1.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 15: blk.1.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 16: blk.1.ffn_down.weight q6_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 17: blk.1.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 18: blk.1.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 19: blk.2.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 20: blk.2.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 21: blk.2.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 22: blk.2.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 23: blk.2.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 24: blk.2.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 25: blk.2.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 26: blk.2.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 27: blk.2.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 28: blk.3.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 29: blk.3.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 30: blk.3.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 31: blk.3.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 32: blk.3.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 33: blk.3.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 34: blk.3.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 35: blk.3.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 36: blk.3.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 37: blk.4.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 38: blk.4.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 39: blk.4.attn_v.weight q6_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 40: blk.4.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 41: blk.4.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 42: blk.4.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 43: blk.4.ffn_down.weight q6_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 44: blk.4.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 45: blk.4.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 46: blk.5.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 47: blk.5.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 48: blk.5.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 49: blk.5.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 50: blk.5.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 51: blk.5.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 52: blk.5.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 53: blk.5.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 54: blk.5.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 55: blk.6.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 56: blk.6.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 57: blk.6.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 58: blk.6.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 59: blk.6.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 60: blk.6.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 61: blk.6.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 62: blk.6.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 63: blk.6.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 64: blk.7.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 65: blk.7.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 66: blk.7.attn_v.weight q6_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 67: blk.7.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 68: blk.7.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 69: blk.7.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 70: blk.7.ffn_down.weight q6_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 71: blk.7.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 72: blk.7.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 73: blk.8.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 74: blk.8.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 75: blk.8.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 76: blk.8.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 77: blk.8.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 78: blk.8.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 79: blk.8.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 80: blk.8.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 81: blk.8.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 82: blk.9.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 83: blk.9.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 84: blk.9.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 85: blk.9.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 86: blk.9.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 87: blk.9.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 88: blk.9.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 89: blk.9.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 90: blk.9.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 91: blk.10.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 92: blk.10.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 93: blk.10.attn_v.weight q6_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 94: blk.10.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 95: blk.10.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 96: blk.10.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 97: blk.10.ffn_down.weight q6_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 98: blk.10.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 99: blk.10.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 100: blk.11.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 101: blk.11.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 102: blk.11.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 103: blk.11.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 104: blk.11.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 105: blk.11.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 106: blk.11.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 107: blk.11.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 108: blk.11.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 109: blk.12.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 110: blk.12.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 111: blk.12.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 112: blk.12.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 113: blk.12.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 114: blk.12.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 115: blk.12.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 116: blk.12.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 117: blk.12.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 118: blk.13.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 119: blk.13.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 120: blk.13.attn_v.weight q6_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 121: blk.13.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 122: blk.13.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 123: blk.13.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 124: blk.13.ffn_down.weight q6_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 125: blk.13.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 126: blk.13.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 127: blk.14.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 128: blk.14.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 129: blk.14.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 130: blk.14.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 131: blk.14.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 132: blk.14.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 133: blk.14.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 134: blk.14.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 135: blk.14.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 136: blk.15.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 137: blk.15.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 138: blk.15.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 139: blk.15.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 140: blk.15.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 141: blk.15.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 142: blk.15.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 143: blk.15.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 144: blk.15.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 145: blk.16.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 146: blk.16.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 147: blk.16.attn_v.weight q6_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 148: blk.16.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 149: blk.16.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 150: blk.16.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 151: blk.16.ffn_down.weight q6_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 152: blk.16.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 153: blk.16.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 154: blk.17.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 155: blk.17.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 156: blk.17.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 157: blk.17.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 158: blk.17.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 159: blk.17.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 160: blk.17.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 161: blk.17.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 162: blk.17.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 163: blk.18.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 164: blk.18.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 165: blk.18.attn_v.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 166: blk.18.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 167: blk.18.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 168: blk.18.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 169: blk.18.ffn_down.weight q5_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 170: blk.18.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 171: blk.18.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 172: blk.19.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 173: blk.19.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 174: blk.19.attn_v.weight q6_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 175: blk.19.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 176: blk.19.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 177: blk.19.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 178: blk.19.ffn_down.weight q6_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 179: blk.19.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 180: blk.19.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 181: blk.20.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 182: blk.20.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 183: blk.20.attn_v.weight q6_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 184: blk.20.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 185: blk.20.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 186: blk.20.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 187: blk.20.ffn_down.weight q6_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 188: blk.20.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 189: blk.20.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 190: blk.21.attn_q.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 191: blk.21.attn_k.weight q5_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 192: blk.21.attn_v.weight q6_K [ 2048, 256, 1, 1 ]
llama_model_loader: - tensor 193: blk.21.attn_output.weight q5_K [ 2048, 2048, 1, 1 ]
llama_model_loader: - tensor 194: blk.21.ffn_gate.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 195: blk.21.ffn_up.weight q5_K [ 2048, 5632, 1, 1 ]
llama_model_loader: - tensor 196: blk.21.ffn_down.weight q6_K [ 5632, 2048, 1, 1 ]
llama_model_loader: - tensor 197: blk.21.attn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 198: blk.21.ffn_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 199: output_norm.weight f32 [ 2048, 1, 1, 1 ]
llama_model_loader: - tensor 200: output.weight q6_K [ 2048, 32003, 1, 1 ]
llama_model_loader: - kv 0: general.architecture str
llama_model_loader: - kv 1: general.name str
llama_model_loader: - kv 2: llama.context_length u32
llama_model_loader: - kv 3: llama.embedding_length u32
llama_model_loader: - kv 4: llama.block_count u32
llama_model_loader: - kv 5: llama.feed_forward_length u32
llama_model_loader: - kv 6: llama.rope.dimension_count u32
llama_model_loader: - kv 7: llama.attention.head_count u32
llama_model_loader: - kv 8: llama.attention.head_count_kv u32
llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32
llama_model_loader: - kv 10: llama.rope.freq_base f32
llama_model_loader: - kv 11: general.file_type u32
llama_model_loader: - kv 12: tokenizer.ggml.model str
llama_model_loader: - kv 13: tokenizer.ggml.tokens arr
llama_model_loader: - kv 14: tokenizer.ggml.scores arr
llama_model_loader: - kv 15: tokenizer.ggml.token_type arr
llama_model_loader: - kv 16: tokenizer.ggml.bos_token_id u32
llama_model_loader: - kv 17: tokenizer.ggml.eos_token_id u32
llama_model_loader: - kv 18: tokenizer.ggml.unknown_token_id u32
llama_model_loader: - kv 19: general.quantization_version u32
llama_model_loader: - type f32: 45 tensors
llama_model_loader: - type q5_K: 135 tensors
llama_model_loader: - type q6_K: 21 tensors
llm_load_print_meta: format = GGUF V2 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = SPM
llm_load_print_meta: n_vocab = 32003
llm_load_print_meta: n_merges = 0
llm_load_print_meta: n_ctx_train = 2048
llm_load_print_meta: n_embd = 2048
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 4
llm_load_print_meta: n_layer = 22
llm_load_print_meta: n_rot = 64
llm_load_print_meta: n_gqa = 8
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
llm_load_print_meta: n_ff = 5632
llm_load_print_meta: freq_base_train = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: model type = ?B
llm_load_print_meta: model ftype = mostly Q5_K - Medium
llm_load_print_meta: model params = 1.10 B
llm_load_print_meta: model size = 745.12 MiB (5.68 BPW)
llm_load_print_meta: general.name = snapshots
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 = 0.06 MB
llm_load_tensors: mem required = 745.19 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 = 11.00 MB
llama_new_context_with_model: compute buffer total size = 72.38 MB
system_info: n_threads = 4 / 8 | AVX = 1 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 |
sampling: repeat_last_n = 64, repeat_penalty = 1.100000, presence_penalty = 0.000000, frequency_penalty = 0.000000, top_k = 40, tfs_z = 1.000000, top_p = 0.950000, typical_p = 1.000000, temp = 0.000000, mirostat = 0, mirostat_lr = 0.100000, mirostat_ent = 5.000000
generate: n_ctx = 512, n_batch = 512, n_predict = -2, n_keep = 0
Please answer in one sentence to this question: What is a Large Language Model?<|im_end|>
¿Qué es un modelo de lenguaje grande?<|im_end|>
<|im_start|>assistant
Un modelo de lenguaje grande es un modelo de aprendizaje automático que se entrena con grandes cantidades de datos de entrenamiento. Esto permite a los modelos de lenguaje grande poder procesar y generar texto de manera más eficiente que los modelos convencionales.
Un ejemplo de modelo de lenguaje grande es el modelo GPT-3 de OpenAI, que se entrenó con 100 billones de palabras. Los modelos de lenguaje grande son utilizados en una amplia variedad de aplicaciones, incluyendo la generación de texto y la resolución de preguntas-respuestas en diferentes áreas, como el lenguaje corporal, la inteligencia artificial y la investigación científica.<|im_end|>
[end of text]
llama_print_timings: load time = 1941.12 ms
llama_print_timings: sample time = 213.20 ms / 219 runs ( 0.97 ms per token, 1027.19 tokens per second)
llama_print_timings: prompt eval time = 304.91 ms / 18 tokens ( 16.94 ms per token, 59.03 tokens per second)
llama_print_timings: eval time = 5176.21 ms / 218 runs ( 23.74 ms per token, 42.12 tokens per second)
llama_print_timings: total time = 5774.74 ms
Log end
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