Can't load model if n-gpu-layers > 0

I'm running this on a Mac mini M2 Pro 16GB. I used the MacOS one-click-installer, and copied the vicuna-13b-v1.5-16k.Q4_K_M model into the models dir. When I select this model, it selects the llama.cpp loader.
If I set the n-gpu-layers parameter to 0, everything works. It doesn't use the GPU though.
If I set it to 1 (or any value other than 0), loading the model produces the following:
2023-09-17 18:38:19 INFO:Loading vicuna-13b-v1.5-16k.Q4_K_M.gguf...
2023-09-17 18:38:19 INFO:llama.cpp weights detected: models/vicuna-13b-v1.5-16k.Q4_K_M.gguf
2023-09-17 18:38:19 INFO:Cache capacity is 0 bytes
llama_model_loader: loaded meta data with 20 key-value pairs and 363 tensors from models/vicuna-13b-v1.5-16k.Q4_K_M.gguf (version GGUF V2 (latest))
llama_model_loader: - tensor    0:                token_embd.weight q4_K     [  5120, 32000,     1,     1 ]
llama_model_loader: - tensor    1:              blk.0.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]
llama_model_loader: - tensor    2:              blk.0.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]
...
llama_model_loader: - tensor  362:                    output.weight q6_K     [  5120, 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:                    llama.rope.scale_linear f32     
llama_model_loader: - kv  11:                          general.file_type u32     
llama_model_loader: - kv  12:                       tokenizer.ggml.model str     
llama_model_loader: - kv  13:                      tokenizer.ggml.tokens arr     
llama_model_loader: - kv  14:                      tokenizer.ggml.scores arr     
llama_model_loader: - kv  15:                  tokenizer.ggml.token_type arr     
llama_model_loader: - kv  16:                tokenizer.ggml.bos_token_id u32     
llama_model_loader: - kv  17:                tokenizer.ggml.eos_token_id u32     
llama_model_loader: - kv  18:            tokenizer.ggml.unknown_token_id u32     
llama_model_loader: - kv  19:               general.quantization_version u32     
llama_model_loader: - type  f32:   81 tensors
llama_model_loader: - type q4_K:  241 tensors
llama_model_loader: - type q6_K:   41 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    = 16384
llm_load_print_meta: n_ctx          = 1048
llm_load_print_meta: n_embd         = 5120
llm_load_print_meta: n_head         = 40
llm_load_print_meta: n_head_kv      = 40
llm_load_print_meta: n_layer        = 40
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           = 13824
llm_load_print_meta: freq_base      = 10000.0
llm_load_print_meta: freq_scale     = 0.25
llm_load_print_meta: model type     = 13B
llm_load_print_meta: model ftype    = mostly Q4_K - Medium
llm_load_print_meta: model size     = 13.02 B
llm_load_print_meta: general.name   = lmsys_vicuna-13b-v1.5-16k
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 =    0.12 MB
llm_load_tensors: mem required  = 7500.97 MB (+  818.75 MB per state)
...................................................................................................
llama_new_context_with_model: kv self size  =  818.75 MB
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M2 Pro
ggml_metal_init: picking default device: Apple M2 Pro
ggml_metal_init: loading '(null)'
ggml_metal_init: error: Error Domain=NSCocoaErrorDomain Code=258 "The file name is invalid."
llama_new_context_with_model: ggml_metal_init() failed
2023-09-17 18:38:19 ERROR:Failed to load the model.
Traceback (most recent call last):
  File "/Users/jhandl/oobabooga_macos/text-generation-webui/modules/ui_model_menu.py", line 194, in load_model_wrapper
    shared.model, shared.tokenizer = load_model(shared.model_name, loader)
  File "/Users/jhandl/oobabooga_macos/text-generation-webui/modules/models.py", line 77, in load_model
    output = load_func_map[loader](model_name)
  File "/Users/jhandl/oobabooga_macos/text-generation-webui/modules/models.py", line 245, in llamacpp_loader
    model, tokenizer = LlamaCppModel.from_pretrained(model_file)
  File "/Users/jhandl/oobabooga_macos/text-generation-webui/modules/llamacpp_model.py", line 87, in from_pretrained
    result.model = Llama(**params)
  File "/Users/jhandl/oobabooga_macos/installer_files/env/lib/python3.10/site-packages/llama_cpp/llama.py", line 334, in __init__
    assert self.ctx is not None
AssertionError

Exception ignored in: <function LlamaCppModel.__del__ at 0x157ee39a0>
Traceback (most recent call last):
  File "/Users/jhandl/oobabooga_macos/text-generation-webui/modules/llamacpp_model.py", line 46, in __del__
    self.model.__del__()
AttributeError: 'LlamaCppModel' object has no attribute 'model'
oobabooga / one-click-installers

Can't load model if n-gpu-layers > 0 #130
