failed to VirtualLock 101449728-byte buffer (after previously locking 17901879296 bytes): Invalid access to memory location

llama.cpp version llama-b2050-bin-win-avx2-x64 version: 2050 (19122117)

Windows 10 Running on AMD 3900x CPU Command: server --threads 23 --ctx-size 16384 --mlock --model models\phind-codellama-34b-python-v1.Q4_K_M.gguf (removing the --ctx-size 16384 --mlock parameters gets rid of the warning but, doesn't fix the error where it exits.)

Happens with all of these models:

https://huggingface.co/TheBloke/Phind-CodeLlama-34B-Python-v1-GGUF/resolve/main/phind-codellama-34b-python-v1.Q4_K_M.gguf?download=true

https://huggingface.co/TheBloke/CodeLlama-34B-Python-GGUF/resolve/main/codellama-34b-python.Q4_K_M.gguf?download=true

https://huggingface.co/senseable/Smaug-72B-v0.1-gguf/resolve/main/Smaug-72B-v0.1-q4_k_m.gguf?download=true

I'm probably doing something stupid or missing something. When I try to run these models, I get the following output and then the program exits:

{"timestamp":1706910929,"level":"INFO","function":"main","line":2428,"message":"build info","build":2050,"commit":"19122117"}
{"timestamp":1706910929,"level":"INFO","function":"main","line":2435,"message":"system info","n_threads":23,"n_threads_batch":-1,"total_threads":24,"system_info":"AVX = 1 | AVX_VNNI = 0 | 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 = 0 | SSE3 = 1 | SSSE3 = 0 | VSX = 0 | "}

llama server listening at http://127.0.0.1:8080

{"timestamp":1706910929,"level":"INFO","function":"main","line":2534,"message":"HTTP server listening","hostname":"127.0.0.1","port":"8080"}
llama_model_loader: loaded meta data with 20 key-value pairs and 435 tensors from models\phind-codellama-34b-python-v1.Q4_K_M.gguf (version GGUF V2)
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = llama
llama_model_loader: - kv   1:                               general.name str              = phind_phind-codellama-34b-python-v1
llama_model_loader: - kv   2:                       llama.context_length u32              = 16384
llama_model_loader: - kv   3:                     llama.embedding_length u32              = 8192
llama_model_loader: - kv   4:                          llama.block_count u32              = 48
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 22016
llama_model_loader: - kv   6:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv   7:                 llama.attention.head_count u32              = 64
llama_model_loader: - kv   8:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                       llama.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  11:                          general.file_type u32              = 15
llama_model_loader: - kv  12:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  13:                      tokenizer.ggml.tokens arr[str,32000]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv  14:                      tokenizer.ggml.scores arr[f32,32000]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  15:                  tokenizer.ggml.token_type arr[i32,32000]   = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv  16:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  17:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  18:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  19:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   97 tensors
llama_model_loader: - type q4_K:  289 tensors
llama_model_loader: - type q6_K:   49 tensors
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
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          = 32000
llm_load_print_meta: n_merges         = 0
llm_load_print_meta: n_ctx_train      = 16384
llm_load_print_meta: n_embd           = 8192
llm_load_print_meta: n_head           = 64
llm_load_print_meta: n_head_kv        = 8
llm_load_print_meta: n_layer          = 48
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_embd_head_k    = 128
llm_load_print_meta: n_embd_head_v    = 128
llm_load_print_meta: n_gqa            = 8
llm_load_print_meta: n_embd_k_gqa     = 1024
llm_load_print_meta: n_embd_v_gqa     = 1024
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
llm_load_print_meta: f_clamp_kqv      = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: n_ff             = 22016
llm_load_print_meta: n_expert         = 0
llm_load_print_meta: n_expert_used    = 0
llm_load_print_meta: rope scaling     = linear
llm_load_print_meta: freq_base_train  = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx  = 16384
llm_load_print_meta: rope_finetuned   = unknown
llm_load_print_meta: model type       = 34B
llm_load_print_meta: model ftype      = Q4_K - Medium
llm_load_print_meta: model params     = 33.74 B
llm_load_print_meta: model size       = 18.83 GiB (4.79 BPW)
llm_load_print_meta: general.name     = phind_phind-codellama-34b-python-v1
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 =    0.17 MiB
llm_load_tensors: offloading 0 repeating layers to GPU
llm_load_tensors: offloaded 0/49 layers to GPU
llm_load_tensors:        CPU buffer size = 19282.48 MiB
........................................................................................warning: failed to VirtualLock 101449728-byte buffer (after previously locking 17901879296 bytes): Invalid access to memory location.

...........
llama_new_context_with_model: n_ctx      = 32000
llama_new_context_with_model: freq_base  = 1000000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init:        CPU KV buffer size =  6000.00 MiB
llama_new_context_with_model: KV self size  = 6000.00 MiB, K (f16): 3000.00 MiB, V (f16): 3000.00 MiB
llama_new_context_with_model:        CPU input buffer size   =    78.63 MiB
llama_new_context_with_model:        CPU compute buffer size =  4452.80 MiB
llama_new_context_with_model: graph splits (measure): 1

ggerganov / llama.cpp

failed to VirtualLock 101449728-byte buffer (after previously locking 17901879296 bytes): Invalid access to memory location #5293