LostRuins / koboldcpp

Run GGUF models easily with a KoboldAI UI. One File. Zero Install.
https://github.com/lostruins/koboldcpp
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[BUG] (v1.4.2) -> WizardLM v1.0 Uncensored: 'blk.0.attn_k.weight' has wrong shape; #419

Closed SabinStargem closed 1 year ago

SabinStargem commented 1 year ago

As the title mentioned, I tried out WizardLM 34b, and it didn't boot up.


Welcome to KoboldCpp - Version 1.42.1 For command line arguments, please refer to --help


Attempting to use CuBLAS library for faster prompt ingestion. A compatible CuBLAS will be required. Initializing dynamic library: koboldcpp_cublas.dll

Overriding thread count, using 6 threads instead. Namespace(bantokens=None, blasbatchsize=2048, blasthreads=6, config=None, contextsize=16384, debugmode=False, forceversion=0, gpulayers=1, highpriority=False, hordeconfig=None, host='', launch=True, lora=None, model=None, model_param='C:/KoboldCPP/Models/wizardlm-1.0-uncensored-codellama-34b.gguf.q4_k_s.bin', noavx2=False, noblas=False, nommap=False, port=5001, port_param=5001, psutil_set_threads=True, ropeconfig=[0.0, 10000.0], skiplauncher=False, smartcontext=False, stream=False, tensor_split=None, threads=6, unbantokens=False, useclblast=None, usecublas=['normal', '0', 'mmq'], usemirostat=None, usemlock=True)

Loading model: C:\KoboldCPP\Models\wizardlm-1.0-uncensored-codellama-34b.gguf.q4_k_s.bin [Threads: 6, BlasThreads: 6, SmartContext: False]


Identified as LLAMA model: (ver 6) Attempting to Load...

Using automatic RoPE scaling (scale:1.000, base:200000.0) System Info: AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 0 | VSX = 0 | ggml_init_cublas: found 1 CUDA devices: Device 0: NVIDIA GeForce RTX 3060, compute capability 8.6 llama_model_loader: loaded meta data with 19 key-value pairs and 435 tensors from C:\KoboldCPP\Models\wizardlm-1.0-uncensored-coY「\ツルtllama_model_loader: - tensor 0: token_embd.weight q4_K [ 8192, 32000, 1, 1 ] llama_model_loader: - tensor 1: blk.0.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 2: blk.0.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 3: blk.0.attn_v.weight q5_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 4: blk.0.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 5: blk.0.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 6: blk.0.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 7: blk.0.ffn_down.weight q5_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 8: blk.0.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 9: blk.0.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 10: blk.1.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 11: blk.1.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 12: blk.1.attn_v.weight q5_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 13: blk.1.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 14: blk.1.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 15: blk.1.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 16: blk.1.ffn_down.weight q5_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 17: blk.1.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 18: blk.1.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 19: blk.2.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 20: blk.2.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 21: blk.2.attn_v.weight q5_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 22: blk.2.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 23: blk.2.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 24: blk.2.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 25: blk.2.ffn_down.weight q5_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 26: blk.2.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 27: blk.2.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 28: blk.3.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 29: blk.3.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 30: blk.3.attn_v.weight q5_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 31: blk.3.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 32: blk.3.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 33: blk.3.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 34: blk.3.ffn_down.weight q5_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 35: blk.3.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 36: blk.3.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 37: blk.4.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 38: blk.4.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 39: blk.4.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 40: blk.4.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 41: blk.4.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 42: blk.4.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 43: blk.4.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 44: blk.4.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 45: blk.4.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 46: blk.5.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 47: blk.5.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 48: blk.5.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 49: blk.5.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 50: blk.5.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 51: blk.5.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 52: blk.5.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 53: blk.5.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 54: blk.5.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 55: blk.6.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 56: blk.6.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 57: blk.6.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 58: blk.6.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 59: blk.6.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 60: blk.6.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 61: blk.6.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 62: blk.6.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 63: blk.6.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 64: blk.7.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 65: blk.7.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 66: blk.7.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 67: blk.7.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 68: blk.7.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 69: blk.7.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 70: blk.7.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 71: blk.7.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 72: blk.7.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 73: blk.8.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 74: blk.8.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 75: blk.8.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 76: blk.8.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 77: blk.8.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 78: blk.8.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 79: blk.8.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 80: blk.8.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 81: blk.8.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 82: blk.9.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 83: blk.9.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 84: blk.9.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 85: blk.9.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 86: blk.9.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 87: blk.9.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 88: blk.9.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 89: blk.9.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 90: blk.9.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 91: blk.10.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 92: blk.10.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 93: blk.10.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 94: blk.10.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 95: blk.10.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 96: blk.10.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 97: blk.10.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 98: blk.10.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 99: blk.10.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 100: blk.11.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 101: blk.11.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 102: blk.11.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 103: blk.11.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 104: blk.11.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 105: blk.11.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 106: blk.11.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 107: blk.11.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 108: blk.11.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 109: blk.12.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 110: blk.12.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 111: blk.12.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 112: blk.12.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 113: blk.12.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 114: blk.12.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 115: blk.12.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 116: blk.12.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 117: blk.12.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 118: blk.13.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 119: blk.13.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 120: blk.13.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 121: blk.13.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 122: blk.13.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 123: blk.13.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 124: blk.13.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 125: blk.13.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 126: blk.13.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 127: blk.14.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 128: blk.14.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 129: blk.14.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 130: blk.14.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 131: blk.14.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 132: blk.14.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 133: blk.14.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 134: blk.14.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 135: blk.14.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 136: blk.15.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 137: blk.15.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 138: blk.15.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 139: blk.15.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 140: blk.15.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 141: blk.15.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 142: blk.15.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 143: blk.15.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 144: blk.15.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 145: blk.16.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 146: blk.16.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 147: blk.16.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 148: blk.16.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 149: blk.16.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 150: blk.16.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 151: blk.16.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 152: blk.16.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 153: blk.16.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 154: blk.17.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 155: blk.17.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 156: blk.17.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 157: blk.17.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 158: blk.17.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 159: blk.17.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 160: blk.17.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 161: blk.17.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 162: blk.17.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 163: blk.18.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 164: blk.18.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 165: blk.18.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 166: blk.18.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 167: blk.18.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 168: blk.18.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 169: blk.18.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 170: blk.18.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 171: blk.18.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 172: blk.19.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 173: blk.19.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 174: blk.19.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 175: blk.19.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - 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tensor 397: blk.44.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 398: blk.44.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 399: blk.44.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 400: blk.44.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 401: blk.44.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 402: blk.44.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 403: blk.44.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 404: blk.44.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 405: blk.44.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 406: blk.45.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 407: blk.45.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 408: blk.45.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 409: blk.45.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 410: blk.45.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 411: blk.45.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 412: blk.45.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 413: blk.45.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 414: blk.45.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 415: blk.46.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 416: blk.46.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 417: blk.46.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 418: blk.46.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 419: blk.46.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 420: blk.46.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 421: blk.46.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 422: blk.46.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 423: blk.46.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 424: blk.47.attn_q.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 425: blk.47.attn_k.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 426: blk.47.attn_v.weight q4_K [ 8192, 1024, 1, 1 ] llama_model_loader: - tensor 427: blk.47.attn_output.weight q4_K [ 8192, 8192, 1, 1 ] llama_model_loader: - tensor 428: blk.47.ffn_gate.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 429: blk.47.ffn_up.weight q4_K [ 8192, 22016, 1, 1 ] llama_model_loader: - tensor 430: blk.47.ffn_down.weight q4_K [ 22016, 8192, 1, 1 ] llama_model_loader: - tensor 431: blk.47.attn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 432: blk.47.ffn_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 433: output_norm.weight f32 [ 8192, 1, 1, 1 ] llama_model_loader: - tensor 434: output.weight q6_K [ 8192, 32000, 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: general.file_type u32 llama_model_loader: - kv 11: tokenizer.ggml.model str llama_model_loader: - kv 12: tokenizer.ggml.tokens arr llama_model_loader: - kv 13: tokenizer.ggml.scores arr llama_model_loader: - kv 14: tokenizer.ggml.token_type arr llama_model_loader: - kv 15: tokenizer.ggml.bos_token_id u32 llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 llama_model_loader: - kv 17: tokenizer.ggml.unknown_token_id u32 llama_model_loader: - kv 18: general.quantization_version u32 llama_model_loader: - type f32: 97 tensors llama_model_loader: - type q4_K: 329 tensors llama_model_loader: - type q5_K: 8 tensors llama_model_loader: - type q6_K: 1 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 = 32000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: n_ctx_train = 4096 llm_load_print_meta: n_ctx = 16384 llm_load_print_meta: n_embd = 8192 llm_load_print_meta: n_head = 64 llm_load_print_meta: n_head_kv = 64 llm_load_print_meta: n_layer = 48 llm_load_print_meta: n_rot = 128 llm_load_print_meta: n_gqa = 1 llm_load_print_meta: f_norm_eps = 1.0e-05 llm_load_print_meta: f_norm_rms_eps = 1.0e-05 llm_load_print_meta: n_ff = 22016 llm_load_print_meta: freq_base = 200000.0 llm_load_print_meta: freq_scale = 1 llm_load_print_meta: model type = 34B llm_load_print_meta: model ftype = mostly Q4_K - Small llm_load_print_meta: model size = 33.74 B llm_load_print_meta: general.name = LLaMA v2 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 = 0.14 MB llm_load_tensors: using CUDA for GPU acceleration error loading model: create_tensor: tensor 'blk.0.attn_k.weight' has wrong shape; expected 8192, 8192, got 8192, 1024, 1\ツルtllama_load_model_from_file: failed to load model gpttype_load_model: error: failed to load model 'C:\KoboldCPP\Models\wizardlm-1.0-uncensored-codellama-34b.gguf.q4_k_s.bin' Load Model OK: False Could not load model: C:\KoboldCPP\Models\wizardlm-1.0-uncensored-codellama-34b.gguf.q4_k_s.bin

[process exited with code 3 (0x00000003)]

LostRuins commented 1 year ago

Who converted this model? n_gqa should be 8 for this model I think.

SabinStargem commented 1 year ago

Venketh. They are probably still learning the ropes, I am guessing? Anyhow, I reported your solution on their model repository. With any luck, this would be fixed up in a jiffy.

https://huggingface.co/venketh/WizardLM-1.0-Uncensored-CodeLlama-34b-GGUF/tree/main

LostRuins commented 1 year ago

I am not entirely sure as 34B was only added upstream recently, and I have not tried running it myself. Lets see what they say first

SabinStargem commented 1 year ago

I tried out The Bloke's version of the model, and it works fine. I am closing this issue, since it was a mishapen model and not a KoboldCPP problem.