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withcatai / catai

Run AI ✨ assistant locally! with simple API for Node.js πŸš€
https://withcatai.github.io/catai/
MIT License
440 stars 28 forks source link

cat dont send answer #50

Closed Gasiorrr closed 7 months ago

Gasiorrr commented 11 months ago

after fix the connection problems. I like to use this chat but after

catai up

i get

C:\Users\ppodl>catai up CatAI client on http://127.0.0.1:3000 New connection llama_model_loader: loaded meta data with 20 key-value pairs and 291 tensors from C:\Users\ppodl\catai\models\vicuna-7b-16k-q4_k_s (version GGUF V2 (latest)) llama_model_loader: - tensor 0: token_embd.weight q4_K [ 4096, 32000, 1, 1 ] llama_model_loader: - tensor 1: blk.0.attn_q.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 2: blk.0.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 3: blk.0.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 4: blk.0.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 5: blk.0.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 6: blk.0.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 7: blk.0.ffn_down.weight q5_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 11: blk.1.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 12: blk.1.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 13: blk.1.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 14: blk.1.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 15: blk.1.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 16: blk.1.ffn_down.weight q5_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 20: blk.2.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 21: blk.2.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 22: blk.2.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 23: blk.2.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 24: blk.2.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 25: blk.2.ffn_down.weight q5_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 29: blk.3.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 30: blk.3.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 31: blk.3.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 32: blk.3.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 33: blk.3.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 34: blk.3.ffn_down.weight q5_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 38: blk.4.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 39: blk.4.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 40: blk.4.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 41: blk.4.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 42: blk.4.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 43: blk.4.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 47: blk.5.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 48: blk.5.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 49: blk.5.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 50: blk.5.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 51: blk.5.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 52: blk.5.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 56: blk.6.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 57: blk.6.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 58: blk.6.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 59: blk.6.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 60: blk.6.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 61: blk.6.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 65: blk.7.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 66: blk.7.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 67: blk.7.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 68: blk.7.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 69: blk.7.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 70: blk.7.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 74: blk.8.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 75: blk.8.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 76: blk.8.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 77: blk.8.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 78: blk.8.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 79: blk.8.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 83: blk.9.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 84: blk.9.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 85: blk.9.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 86: blk.9.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 87: blk.9.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 88: blk.9.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 92: blk.10.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 93: blk.10.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 94: blk.10.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 95: blk.10.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 96: blk.10.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 97: blk.10.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 101: blk.11.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 102: blk.11.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 103: blk.11.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 104: blk.11.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 105: blk.11.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 106: blk.11.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 110: blk.12.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 111: blk.12.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 112: blk.12.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 113: blk.12.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 114: blk.12.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 115: blk.12.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 119: blk.13.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 120: blk.13.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 121: blk.13.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 122: blk.13.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 123: blk.13.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 124: blk.13.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 128: blk.14.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 129: blk.14.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 130: blk.14.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 131: blk.14.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 132: blk.14.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 133: blk.14.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 137: blk.15.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 138: blk.15.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 139: blk.15.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 140: blk.15.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 141: blk.15.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 142: blk.15.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 146: blk.16.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 147: blk.16.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 148: blk.16.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 149: blk.16.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 150: blk.16.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 151: blk.16.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 155: blk.17.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 156: blk.17.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 157: blk.17.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 158: blk.17.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 159: blk.17.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 160: blk.17.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 164: blk.18.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 165: blk.18.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 166: blk.18.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 167: blk.18.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 168: blk.18.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 169: blk.18.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 173: blk.19.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 174: blk.19.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 175: blk.19.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 176: blk.19.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 177: blk.19.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 178: blk.19.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 182: blk.20.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 183: blk.20.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 184: blk.20.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 185: blk.20.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 186: blk.20.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 187: blk.20.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 191: blk.21.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 192: blk.21.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 193: blk.21.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 194: blk.21.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 195: blk.21.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 196: blk.21.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 200: blk.22.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 201: blk.22.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 202: blk.22.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 203: blk.22.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 204: blk.22.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 205: blk.22.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 209: blk.23.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 210: blk.23.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 211: blk.23.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 212: blk.23.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 213: blk.23.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 214: blk.23.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 218: blk.24.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 219: blk.24.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 220: blk.24.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 221: blk.24.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 222: blk.24.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 223: blk.24.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 227: blk.25.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 228: blk.25.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 229: blk.25.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 230: blk.25.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 231: blk.25.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 232: blk.25.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 236: blk.26.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 237: blk.26.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 238: blk.26.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 239: blk.26.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 240: blk.26.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 241: blk.26.ffn_down.weight q4_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 q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 245: blk.27.attn_k.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 246: blk.27.attn_v.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 247: blk.27.attn_output.weight q4_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 248: blk.27.ffn_gate.weight q4_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 249: blk.27.ffn_up.weight q4_K [ 4096, 11008, 1, 1 ]....

but after ask and send 1st qestion i dont get answer and the loading animation is loop

Gasiorrr commented 11 months ago

by the way the red button to stop dont work :P

ido-pluto commented 11 months ago

Does the cli hang up? I am currently checking on my old x64 Windows 10 machine with the same model: vicuna-7b-16k-q4_k_s, and it is slow...

How much RAM do you have? What CPU do you have? How many cors of CPU and GPU do you have? What version of nodejs do you use?

Can you try to install this model?

catai install https://huggingface.co/TheBloke/wizardLM-7B-GGUF/resolve/main/wizardLM-7B.Q2_K.gguf

It is lighter and has a smaller context. I think you do not have enough memory to run a 16k content model

Does your CPU stay high after you send the prompt, it might just be slow because your GPU is not involved

Is it faster to run it with WSL?

Gasiorrr commented 11 months ago

image

Gasiorrr commented 11 months ago

on termux on my S8+ this script work good but on me laptop windows 11 dont.

Intel(R) Celeron(R) N4020 CPU @ 1.10GHz 1.10 GHz RAM: 8.00 GB (dostΔ™pne: 7.66 GB)

ido-pluto commented 10 months ago

llama.cpp is optimised for arm processors, which is why CatAI on your phone runs faster. I do not think the CPU on your laptop is capable of running llama.cpp, you might want a stronger CPU and preferably an ARM CPU

Gasiorrr commented 10 months ago

on wizard i run catai on pc dont work ^^ :P

On Fri, 13 Oct 2023 at 12:14, Ido S. @.***> wrote:

Closed #50 https://github.com/withcatai/catai/issues/50 as completed.

β€” Reply to this email directly, view it on GitHub https://github.com/withcatai/catai/issues/50#event-10642586655, or unsubscribe https://github.com/notifications/unsubscribe-auth/AWSPOMOR3TBYMKSCBWHKNTDX7EH6ZAVCNFSM6AAAAAA5ZF5FU6VHI2DSMVQWIX3LMV45UABCJFZXG5LFIV3GK3TUJZXXI2LGNFRWC5DJN5XDWMJQGY2DENJYGY3DKNI . You are receiving this because you authored the thread.Message ID: @.***>

Gasiorrr commented 10 months ago

sorry on samsung work on pc dont :D

On Fri, 13 Oct 2023 at 12:51, 4 Fun @.***> wrote:

on wizard i run catai on pc dont work ^^ :P

On Fri, 13 Oct 2023 at 12:14, Ido S. @.***> wrote:

Closed #50 https://github.com/withcatai/catai/issues/50 as completed.

β€” Reply to this email directly, view it on GitHub https://github.com/withcatai/catai/issues/50#event-10642586655, or unsubscribe https://github.com/notifications/unsubscribe-auth/AWSPOMOR3TBYMKSCBWHKNTDX7EH6ZAVCNFSM6AAAAAA5ZF5FU6VHI2DSMVQWIX3LMV45UABCJFZXG5LFIV3GK3TUJZXXI2LGNFRWC5DJN5XDWMJQGY2DENJYGY3DKNI . You are receiving this because you authored the thread.Message ID: @.***>

sarfraznawaz2005 commented 7 months ago

I am having same issue, it just shows loading bar on cli as well as web app. I have 32 gb ram and 4gb nvidia graphic card with intell processor.

ido-pluto commented 7 months ago

Try to install catai beta with

npm i -g catai@beta

Then recompile the binaries with

catai cpp

A stable version of compiled binaries will be released soon

sarfraznawaz2005 commented 7 months ago

already tried that seeing other issues, didn't work, same error. I am currently downloading another small model to see if it works with that. Thanks

sarfraznawaz2005 commented 7 months ago

unfortunately didn't work with @beta stuff too. Here is output:

`C:\Users\Sarfraz>catai cpp Repo: ggerganov/llama.cpp Release: b1567

βœ” Removed existing llama.cpp directory Cloning llama.cpp Clone ggerganov/llama.cpp (local bundle) 100% β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ 0s β—· Downloading cmake @xpack-dev-tools/cmake@3.26.5-1.1... @xpack-dev-tools/cmake@3.26.5-1.1 => 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1' Downloading https://github.com/xpack-dev-tools/cmake-xpack/releases/download/v3.26.5-1/xpack-cmake-3.26.5-1-win32-x64.zip... Extracting 'xpack-cmake-3.26.5-1-win32-x64.zip'... 3306 files => 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1.content' 'xpacks\@xpack-dev-tools\cmake' -> 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1' 'xpacks.bin\cmake.cmd' -> 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1.content\bin\cmake.exe' 'xpacks.bin\cmake.ps1' -> 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1.content\bin\cmake.exe' 'xpacks.bin\cmake' -> 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1.content\bin\cmake.exe' 'xpacks.bin\cpack.cmd' -> 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1.content\bin\cpack.exe' 'xpacks.bin\cpack.ps1' -> 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1.content\bin\cpack.exe' 'xpacks.bin\cpack' -> 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1.content\bin\cpack.exe' 'xpacks.bin\ctest.cmd' -> 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1.content\bin\ctest.exe' 'xpacks.bin\ctest.ps1' -> 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1.content\bin\ctest.exe' 'xpacks.bin\ctest' -> 'C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\xpack\store\@xpack-dev-tools\cmake\3.26.5-1.1.content\bin\ctest.exe' βœ” Downloaded cmake β—· Compiling llama.cpp Not searching for unused variables given on the command line. -- Selecting Windows SDK version 10.0.22621.0 to target Windows 6.2.9200. -- The C compiler identification is MSVC 19.38.33134.0 -- The CXX compiler identification is MSVC 19.38.33134.0 -- Detecting C compiler ABI info -- Detecting C compiler ABI info - done -- Check for working C compiler: C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.38.33130/bin/Hostx64/x64/cl.exe - skipped -- Detecting C compile features -- Detecting C compile features - done -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Check for working CXX compiler: C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.38.33130/bin/Hostx64/x64/cl.exe - skipped -- Detecting CXX compile features -- Detecting CXX compile features - done -- Performing Test CMAKE_HAVE_LIBC_PTHREAD -- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Failed -- Looking for pthread_create in pthreads -- Looking for pthread_create in pthreads - not found -- Looking for pthread_create in pthread -- Looking for pthread_create in pthread - not found -- Found Threads: TRUE -- CMAKE_SYSTEM_PROCESSOR: AMD64 -- CMAKE_GENERATOR_PLATFORM: x64 -- x86 detected -- Performing Test HAS_AVX_1 -- Performing Test HAS_AVX_1 - Success -- Performing Test HAS_AVX2_1 -- Performing Test HAS_AVX2_1 - Success -- Performing Test HAS_FMA_1 -- Performing Test HAS_FMA_1 - Success -- Performing Test HAS_AVX512_1 -- Performing Test HAS_AVX512_1 - Failed -- Performing Test HAS_AVX512_2 -- Performing Test HAS_AVX512_2 - Failed Microsoft (R) Library Manager Version 14.38.33134.0 Copyright (C) Microsoft Corporation. All rights reserved.

Creating library C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\node.lib and object C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\node.exp -- Configuring done (26.8s) -- Generating done (0.1s) -- Build files have been written to: C:/Users/Sarfraz/AppData/Roaming/npm/node_modules/catai/node_modules/node-llama-cpp/llama/build MSBuild version 17.8.5+b5265ef37 for .NET Framework

Checking Build System Generating build details from Git -- Found Git: C:/Program Files/Git/cmd/git.exe (found version "2.43.0.windows.1") Building Custom Rule C:/Users/Sarfraz/AppData/Roaming/npm/node_modules/catai/node_modules/node-llama-cpp/llama/llama.cpp/common/CMakeLists.txt build-info.cpp build_info.vcxproj -> C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\common\build_info.dir\Release\bu ild_info.lib Building Custom Rule C:/Users/Sarfraz/AppData/Roaming/npm/node_modules/catai/node_modules/node-llama-cpp/llama/llama.cpp/CMakeLists.txt ggml.c ggml-alloc.c ggml-backend.c ggml-quants.c Generating Code... C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\ggml-backend.c(875,21): warning C4477: 'fprintf' : format stri ng '%lu' requires an argument of type 'unsigned long', but variadic argument 1 has type 'unsigned __int64' [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\cata i\node_modules\node-llama-cpp\llama\build\llama.cpp\ggml.vcxproj] C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\ggml-backend.c(875,21): consider using '%llu' in the format string C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\ggml-backend.c(875,21): consider using '%Iu' in the format string C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\ggml-backend.c(875,21): consider using '%I64u' in the format string

C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\ggml-quants.c(627,26): warning C4244: '=': conversion from 'fl oat' to 'int8_t', possible loss of data [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\ggml.vcxproj] C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\ggml-quants.c(845,36): warning C4244: '=': conversion from 'fl oat' to 'int8_t', possible loss of data [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\ggml.vcxproj] C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\ggml-quants.c(846,36): warning C4244: '=': conversion from 'fl oat' to 'int8_t', possible loss of data [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\ggml.vcxproj] ggml.vcxproj -> C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\ggml.dir\Release\ggml.lib Building Custom Rule C:/Users/Sarfraz/AppData/Roaming/npm/node_modules/catai/node_modules/node-llama-cpp/llama/llama.cpp/CMakeLists.txt llama.cpp C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\llama.cpp(1190,31): warning C4305: 'initializing': truncation from 'double' to 'float' [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\llama.vcxproj] C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\llama.cpp(2466,69): warning C4566: character represented by un iversal-character-name '\u010A' cannot be represented in the current code page (1252) [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-l lama-cpp\llama\build\llama.cpp\llama.vcxproj] C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\llama.cpp(9574,28): warning C4146: unary minus operator applie d to unsigned type, result still unsigned [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\llama.vcxproj ] C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\llama.cpp(9604,28): warning C4146: unary minus operator applie d to unsigned type, result still unsigned [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\llama.vcxproj ] llama.vcxproj -> C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\Release\llama.lib Building Custom Rule C:/Users/Sarfraz/AppData/Roaming/npm/node_modules/catai/node_modules/node-llama-cpp/llama/llama.cpp/common/CMakeLists.txt common.cpp sampling.cpp C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\common\sampling.cpp(75,45): warning C4267: 'initializing': con version from 'size_t' to 'int', possible loss of data [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\c ommon\common.vcxproj] C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\common\sampling.cpp(75,20): warning C4267: 'initializing': con version from 'size_t' to 'const int', possible loss of data [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama .cpp\common\common.vcxproj] console.cpp C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\common\console.cpp(253,30): warning C4267: 'initializing': con version from 'size_t' to 'DWORD', possible loss of data [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp \common\common.vcxproj] C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\common\console.cpp(407,28): warning C4267: 'initializing': con version from 'size_t' to 'int', possible loss of data [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\c ommon\common.vcxproj] grammar-parser.cpp train.cpp Generating Code... C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\common\common.cpp(887): warning C4715: 'gpt_random_prompt': no t all control paths return a value [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\common\common.vcxpro j] common.vcxproj -> C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\common\Release\common.lib Building Custom Rule C:/Users/Sarfraz/AppData/Roaming/npm/node_modules/catai/node_modules/node-llama-cpp/llama/llama.cpp/CMakeLists.txt ggml_static.vcxproj -> C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama.cpp\Release\ggml_static.lib Building Custom Rule C:/Users/Sarfraz/AppData/Roaming/npm/node_modules/catai/node_modules/node-llama-cpp/llama/CMakeLists.txt addon.cpp C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\common\log.h(396,19): warning C4996: 'fopen': This function or variable may be unsafe. Consider using fopen_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details. [C:\Users\Sarfraz\AppDa ta\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama-addon.vcxproj] (compiling source file '../addon.cpp')

C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\llama.cpp\common\log.h(404,97): warning C4996: 'strerror': This function or variable may be unsafe. Consider using strerror_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details. [C:\Users\Sarfraz \AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama-addon.vcxproj] (compiling source file '../addon.cpp')

C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\addon.cpp(14,87): warning C4267: 'argument': conversion from 'size_t' to 'int', possible loss of data [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama-addon.vcxproj] C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\addon.cpp(17,82): warning C4267: 'argument': conversion from 'size_t' to 'int', possible loss of data [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama-addon.vcxproj] C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\addon.cpp(479,100): warning C4267: 'argument': conversion from 'size_t' to 'llama_pos', possible loss of data [C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\llama-addon.vcxproj] win_delay_load_hook.cc Generating Code... Creating library C:/Users/Sarfraz/AppData/Roaming/npm/node_modules/catai/node_modules/node-llama-cpp/llama/build/Release/llama-addon.lib and object C:/Users/ Sarfraz/AppData/Roaming/npm/node_modules/catai/node_modules/node-llama-cpp/llama/build/Release/llama-addon.exp llama-addon.vcxproj -> C:\Users\Sarfraz\AppData\Roaming\npm\node_modules\catai\node_modules\node-llama-cpp\llama\build\Release\llama-addon.node Building Custom Rule C:/Users/Sarfraz/AppData/Roaming/npm/node_modules/catai/node_modules/node-llama-cpp/llama/CMakeLists.txt βœ” Compiled llama.cpp

Repo: ggerganov/llama.cpp Release: b1567

Done

C:\Users\Sarfraz>catai up CatAI client on http://127.0.0.1:3000 New connection llama_model_loader: loaded meta data with 19 key-value pairs and 291 tensors from C:\Users\Sarfraz\catai\models\wizardLM-7B.Q2_K.gguf (version GGUF V2) llama_model_loader: - tensor 0: token_embd.weight q2_K [ 4096, 32001, 1, 1 ] llama_model_loader: - tensor 1: blk.0.attn_q.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 2: blk.0.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 3: blk.0.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 4: blk.0.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 5: blk.0.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 6: blk.0.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 7: blk.0.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 11: blk.1.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 12: blk.1.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 13: blk.1.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 14: blk.1.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 15: blk.1.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 16: blk.1.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 20: blk.2.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 21: blk.2.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 22: blk.2.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 23: blk.2.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 24: blk.2.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 25: blk.2.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 29: blk.3.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 30: blk.3.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 31: blk.3.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 32: blk.3.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 33: blk.3.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 34: blk.3.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 38: blk.4.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 39: blk.4.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 40: blk.4.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 41: blk.4.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 42: blk.4.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 43: blk.4.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 47: blk.5.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 48: blk.5.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 49: blk.5.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 50: blk.5.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 51: blk.5.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 52: blk.5.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 56: blk.6.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 57: blk.6.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 58: blk.6.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 59: blk.6.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 60: blk.6.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 61: blk.6.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 65: blk.7.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 66: blk.7.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 67: blk.7.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 68: blk.7.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 69: blk.7.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 70: blk.7.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 74: blk.8.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 75: blk.8.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 76: blk.8.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 77: blk.8.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 78: blk.8.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 79: blk.8.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 83: blk.9.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 84: blk.9.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 85: blk.9.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 86: blk.9.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 87: blk.9.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 88: blk.9.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 92: blk.10.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 93: blk.10.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 94: blk.10.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 95: blk.10.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 96: blk.10.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 97: blk.10.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 101: blk.11.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 102: blk.11.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 103: blk.11.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 104: blk.11.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 105: blk.11.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 106: blk.11.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 110: blk.12.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 111: blk.12.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 112: blk.12.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 113: blk.12.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 114: blk.12.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 115: blk.12.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 119: blk.13.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 120: blk.13.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 121: blk.13.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 122: blk.13.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 123: blk.13.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 124: blk.13.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 128: blk.14.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 129: blk.14.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 130: blk.14.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 131: blk.14.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 132: blk.14.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 133: blk.14.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 137: blk.15.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 138: blk.15.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 139: blk.15.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 140: blk.15.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 141: blk.15.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 142: blk.15.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 146: blk.16.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 147: blk.16.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 148: blk.16.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 149: blk.16.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 150: blk.16.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 151: blk.16.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 155: blk.17.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 156: blk.17.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 157: blk.17.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 158: blk.17.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 159: blk.17.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 160: blk.17.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 164: blk.18.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 165: blk.18.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 166: blk.18.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 167: blk.18.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 168: blk.18.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 169: blk.18.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 173: blk.19.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 174: blk.19.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 175: blk.19.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 176: blk.19.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 177: blk.19.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 178: blk.19.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 182: blk.20.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 183: blk.20.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 184: blk.20.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 185: blk.20.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 186: blk.20.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 187: blk.20.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 191: blk.21.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - 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tensor 231: blk.25.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 232: blk.25.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 236: blk.26.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 237: blk.26.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 238: blk.26.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 239: blk.26.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 240: blk.26.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 241: blk.26.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 245: blk.27.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 246: blk.27.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 247: blk.27.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 248: blk.27.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 249: blk.27.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 250: blk.27.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 254: blk.28.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 255: blk.28.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 256: blk.28.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 257: blk.28.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 258: blk.28.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 259: blk.28.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 263: blk.29.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 264: blk.29.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 265: blk.29.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 266: blk.29.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 267: blk.29.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 268: blk.29.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 272: blk.30.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 273: blk.30.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 274: blk.30.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 275: blk.30.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 276: blk.30.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 277: blk.30.ffn_up.weight q3_K [ 4096, 11008, 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 q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 281: blk.31.attn_k.weight q2_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 282: blk.31.attn_v.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 283: blk.31.attn_output.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 284: blk.31.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 285: blk.31.ffn_down.weight q3_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 286: blk.31.ffn_up.weight q3_K [ 4096, 11008, 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, 32001, 1, 1 ] llama_model_loader: - kv 0: general.architecture str = llama llama_model_loader: - kv 1: general.name str = wizardlm_wizardlm-7b-v1.0 llama_model_loader: - kv 2: llama.context_length u32 = 2048 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: general.file_type u32 = 10 llama_model_loader: - kv 11: tokenizer.ggml.model str = llama llama_model_loader: - kv 12: tokenizer.ggml.tokens arr[str,32001] = ["", "", "", "<0x00>", "<... llama_model_loader: - kv 13: tokenizer.ggml.scores arr[f32,32001] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,32001] = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ... llama_model_loader: - kv 15: tokenizer.ggml.bos_token_id u32 = 1 llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 2 llama_model_loader: - kv 17: tokenizer.ggml.unknown_token_id u32 = 0 llama_model_loader: - kv 18: general.quantization_version u32 = 2 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q2_K: 65 tensors llama_model_loader: - type q3_K: 160 tensors llama_model_loader: - type q6_K: 1 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 = 2048 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 = 10000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_yarn_orig_ctx = 2048 llm_load_print_meta: rope_finetuned = unknown llm_load_print_meta: model type = 7B llm_load_print_meta: model ftype = mostly Q2_K llm_load_print_meta: model params = 6.74 B llm_load_print_meta: model size = 2.63 GiB (3.35 BPW) llm_load_print_meta: general.name = wizardlm_wizardlm-7b-v1.0 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: LF token = 13 '<0x0A>' llm_load_tensors: ggml ctx size = 0.11 MiB llm_load_tensors: mem required = 2694.43 MiB ................................................................................................. llama_new_context_with_model: n_ctx = 4096 llama_new_context_with_model: freq_base = 10000.0 llama_new_context_with_model: freq_scale = 1 llama_new_context_with_model: kv self size = 2048.00 MiB llama_build_graph: non-view tensors processed: 740/740 llama_new_context_with_model: compute buffer total size = 2307.09 MiB β–…β–…β–…β–…β–…β–…β–…β–…β–…β–…β–…β–…^C C:\Users\Sarfraz>`

ido-pluto commented 7 months ago

Can you try the following?

npx node-llama-cpp@beta build
npx node-llama-cpp@beta chat --model "C:\Users\Sarfraz\catai\models\wizardLM-7B.Q2_K.gguf"

This will compile and run a CLI chat with the latest binaries binding.

If that does not work, also try this:

npx node-llama-cpp@beta download
npx node-llama-cpp@beta chat --model "C:\Users\Sarfraz\catai\models\wizardLM-7B.Q2_K.gguf"

This will compile with the latest version of llama.cpp

Please tell me what works for you :)

ido-pluto commented 7 months ago

Do you know if it worked? I see the AI replied something - maybe this is the model, do you have the original download link so I will try this myself?

sarfraznawaz2005 commented 7 months ago

it is replying with loading animation bar as can be seen in output on both cli and web so it didn't work. I tried with two different models, same output.

AI: β–…β–…β–…β–…β–…β–…β–…β–…β–…β–…β–…β–…β–…β–…β–…β–…

That loading bar keeps on going, never ends on cli or web.

ido-pluto commented 7 months ago

This is super wired, I really think it is the model just outputting this instant of a normal text.

Please try to install another model and test it again

catai install uncensored-frank-7b-q4_k_s
npx node-llama-cpp@beta chat --model "C:\Users\Sarfraz\catai\models\uncensored-frank-7b-q4_k_s.gguf"

For some reason, for me it download the model without a gguf file extension, so maybe the right command is this:

npx node-llama-cpp@beta chat --model "C:\Users\Sarfraz\catai\models\uncensored-frank-7b-q4_k_s"
sarfraznawaz2005 commented 7 months ago

you are right, don't know why this happend, i had installed those models with install command. I checked with another model saved for gpt4all (mistral-7b-openorca.Q4_0.gguf), it worked with that. Thanks a lot 😊

ido-pluto commented 7 months ago

You welcome :)