Row_split not work in IK_version. #7489

11:19:14-446715 INFO     Starting Text Generation Web UI
11:19:14-451554 INFO     Loading settings from "user_data\settings.yaml"
11:19:16-752781 INFO     OpenAI/Anthropic-compatible API URL:

                         http://127.0.0.1:5000/v1


Running on local URL:  http://127.0.0.1:7860

11:19:27-823631 INFO     Loading
                         "TheDrummer_Behemoth-R1-123B-v2-GGUF\TheDrummer_Behemoth-R1-123B-v2-Q4_K_M-00001-of-00002.gguf
                         "
11:19:27-829767 INFO     Using gpu_layers=auto | ctx_size=8192 | cache_type=fp16
error: invalid parameter for argument: --split-mode
usage: C:\Users\PC2\Desktop\textgen-portable-ik-4.4-windows-cuda13.1\text-generation-webui-ik-4.4\portable_env\Lib\site-packages\ik_llama_cpp_binaries\bin\llama-server.exe [options]

general:

  -h,    --help, --usage          print usage and exit
         --version                show version and build info
  -v,    --verbose                print verbose information
         --minilog                print important information
         --verbosity N            set specific verbosity level (default: 0)
         --verbose-prompt         print a verbose prompt before generation (default: false)
  -dr,   --dry-run                skip loading tensors in the files
         --no-display-prompt      don't print prompt at generation (default: false)
  -co,   --color                  colorise output to distinguish prompt and user input from generations (default: false)
  -s,    --seed SEED              RNG seed (default: -1, use random seed for < 0)
  -t,    --threads N              number of threads to use during generation (default: 8)
  -tb,   --threads-batch N        number of threads to use during batch and prompt processing (default: same as --threads)
  -td,   --threads-draft N        number of threads to use during generation (default: same as --threads)
  -tbd,  --threads-batch-draft N  number of threads to use during batch and prompt processing (default: same as --threads-draft)
  -ps,   --p-split N              speculative decoding split probability (default: 0.1)
  -lcs,  --lookup-cache-static FNAME
                                  path to static lookup cache to use for lookup decoding (not updated by generation)
  -lcd,  --lookup-cache-dynamic FNAME
                                  path to dynamic lookup cache to use for lookup decoding (updated by generation)
  -c,    --ctx-size N             size of the prompt context (default: 0, 0 = loaded from model)
  -cd,   --ctx-size-draft N       size of the prompt context for the draft model (default: 0, 0 = loaded from model)
  --ctx-checkpoints N             max number of context checkpoints to create per slot (default: 32)
  --ctx-checkpoints-interval N    minimum number of tokens between each context checkpoint.  (default: 512, <=0 disable)
  --ctx-checkpoints-tolerance N   the number of tokens before the full prompt to create the checkpoint.  (default: 5, <=0 disable)
  -cram, --cache-ram N            set the maximum cache size in MiB (default: 8192, -1 - no limit, 0 - disable)
  -crs,  --cache-ram-similarity N
                                  max of similarity of prompt tokens to cache tokens that triggers prompt cache (default: 0.50).
  -cram-n-min --cache-ram-n-min N
                                  minimum number of the cached tokens that triggers prompt cache (default: 0).
  -n,    --predict N              number of tokens to predict (default: -1, -1 = infinity, -2 = until context filled)
  -b,    --batch-size N           logical maximum batch size (default: 2048)
  -ub,   --ubatch-size N          physical maximum batch size (default: 512)
         --keep N                 number of tokens to keep from the initial prompt (default: 0, -1 = all)
         --chunks N               max number of chunks to process (default: -1, -1 = all)
  -no-fa, --no-flash-attn         disable Flash Attention (default: enabled)
  -fa, --flash-attn (auto|on|off|0|1)
                                  set Flash Attention (default: on)
  -mla,  --mla-use                enable MLA (default: 3)
  -amb,  --attention-max-batch    max batch size for attention computations (default: 0)
  -no-fmoe, --no-fused-moe        disable fused MoE (default: enabled)
  -ger,  --grouped-expert-routing
                                  enable grouped expert routing (default: disabled)
  -no-fug, --no-fused-up-gate     disable fused up-gate (default: enabled)
  -no-mmad, --no-fused-mul-multiadd
                                  disable fused mul-multi_add (default: enabled)
  -gr, --graph-reuse              enable graph reuse (default: enabled)
  -no-gr, --no-graph-reuse        disable graph reuse (default: disabled)
  -ser,  --smart-expert-reduction
                                  experts reduction (default: -1,0)
  -mqkv,  --merge-qkv,            merge Q,K,V (default: 0)
  -muge,  --merge-up-gate-experts,
                                  merge ffn_up/gate_exps (default: 0)
  -khad,  --k-cache-hadamard,     Use Hadamard transform for K-cache (default: 0)
  -vhad,  --v-cache-hadamard,     Use Hadamard transform for V-cache (default: 0)
  -smf16, --split-mode-f16,       Use f16 for data exchange between GPUs (default: 1)
  -smf32, --split-mode-f32,       Use f32 for data exchange between GPUs (default: 0)
  -grt, --graph-reduce-type       Type for data exchange between GPUs (default: f32)
  -smgs, --split-mode-graph-scheduling,
                                  Force Split Mode Graph Scheduling (default: 0)
  -sas,  --scheduler_async,       Async evaluation of compute graphs: 0)
  -vq, --validate-quants          validate quantized data while loading the model (default: 0)
  -p,    --prompt PROMPT          prompt to start generation with
                                  in conversation mode, this will be used as system prompt
                                  (default: '')
  -f,    --file FNAME             a file containing the prompt (default: none)
         --in-file FNAME          an input file (repeat to specify multiple files)
  -bf,   --binary-file FNAME      binary file containing the prompt (default: none)
  -e,    --escape                 process escapes sequences (\n, \r, \t, \', \", \\) (default: true)
         --no-escape              do not process escape sequences
  -ptc,  --print-token-count N    print token count every N tokens (default: -1)
         --prompt-cache FNAME     file to cache prompt state for faster startup (default: none)
         --prompt-cache-all       if specified, saves user input and generations to cache as well
                                  not supported with --interactive or other interactive options
         --prompt-cache-ro        if specified, uses the prompt cache but does not update it
  -r,    --reverse-prompt PROMPT  halt generation at PROMPT, return control in interactive mode
                                  can be specified more than once for multiple prompts
  -sp,   --special                special tokens output enabled (default: false)
  -cnv,  --conversation           run in conversation mode, does not print special tokens and suffix/prefix
                                  if suffix/prefix are not specified, default chat template will be used
                                  (default: false)
  -i,    --interactive            run in interactive mode (default: false)
  -if,   --interactive-first      run in interactive mode and wait for input right away (default: false)
  -mli,  --multiline-input        allows you to write or paste multiple lines without ending each in '\'
         --in-prefix-bos          prefix BOS to user inputs, preceding the `--in-prefix` string
         --in-prefix STRING       string to prefix user inputs with (default: empty)
         --in-suffix STRING       string to suffix after user inputs with (default: empty)
         --no-warmup              skip warming up the model with an empty run
         --spm-infill             use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this. (default: disabled)

sampling:

         --samplers SAMPLERS      samplers that will be used for generation in the order, separated by ';'
                                  (default: dry;top_k;tfs_z;typical_p;top_p;min_p;xtc;top_n_sigma;temperature;adaptive_p;)
         --sampling-seq SEQUENCE  simplified sequence for samplers that will be used (default: dkfypmxntws)
         --ignore-eos             ignore end of stream token and continue generating (implies --logit-bias EOS-inf)
         --penalize-nl            penalize newline tokens (default: false)
         --temp N                 temperature (default: 0.8)
         --top-k N                top-k sampling (default: 40, 0 = disabled)
         --top-p N                top-p sampling (default: 0.9, 1.0 = disabled)
         --min-p N                min-p sampling (default: 0.1, 0.0 = disabled)
         --tfs N                  tail free sampling, parameter z (default: 1.0, 1.0 = disabled)
         --typical N              locally typical sampling, parameter p (default: 1.0, 1.0 = disabled)
         --repeat-last-n N        last n tokens to consider for penalize (default: 64, 0 = disabled, -1 = ctx_size)
         --repeat-penalty N       penalize repeat sequence of tokens (default: 1.0, 1.0 = disabled)
         --presence-penalty N     repeat alpha presence penalty (default: 0.0, 0.0 = disabled)
         --frequency-penalty N    repeat alpha frequency penalty (default: 0.0, 0.0 = disabled)
         --dynatemp-range N       dynamic temperature range (default: 0.0, 0.0 = disabled)
         --dynatemp-exp N         dynamic temperature exponent (default: 1.0)
         --mirostat N             use Mirostat sampling.
                                  Top K, Nucleus, Tail Free and Locally Typical samplers are ignored if used.
                                  (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)
         --mirostat-lr N          Mirostat learning rate, parameter eta (default: 0.1)
         --mirostat-ent N         Mirostat target entropy, parameter tau (default: 5.0)
         --xtc-probability p      xtc probability (default: 0.0, 0.0 = disabled)
         --xtc-threshold t        xtc threshold (default: 1.0, >0.5 = disabled)
         --top-n-sigma t          top-n-sigma parmeter (default: 0.0, 0.0 = disabled)
         --adaptive-target        adaptive-p sampling: (default: -1.00, <0.0 = disabled)
         --adaptive-decay         adaptive-p sampling: (default: 0.90)
         --banned-string-file     file path of the list of banned strings on each line
         --banned-n               number of tokens banned in the phrase during rewind. -1 means all tokens: (default: 1)
         --adaptive-updt-w-cur    adaptive-p sampling: (default: false)
         -l TOKEN_ID(+/-)BIAS     modifies the likelihood of token appearing in the completion,
                                  i.e. `--logit-bias 15043+1` to increase likelihood of token ' Hello',
                                  or `--logit-bias 15043-1` to decrease likelihood of token ' Hello'
         --cfg-negative-prompt PROMPT
                                  negative prompt to use for guidance (default: '')
         --cfg-negative-prompt-file FNAME
                                  negative prompt file to use for guidance
         --cfg-scale N            strength of guidance (default: 1.0, 1.0 = disable)

template:

         --jinja                  set custom jinja chat template (default: template taken from model's metadata)
                                  if suffix/prefix are specified, template will be disabled
                                  only commonly used templates are accepted:
                                  https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template
         --peg                    use peg parser for qwen3.5 models.
                                  https://github.com/ikawrakow/ik_llama.cpp/pull/1490
         --chat-template JINJA_TEMPLATE
                                  use jinja template for chat (default: disabled)

         --chat-template-file file_with_JINJA_TEMPLATE
                                  load jinja template for chat from the file

         --reasoning-format FORMAT
                                  controls whether thought tags are allowed and/or extracted from the response, and in which format they're returned; one of:
                                  - none: leaves thoughts unparsed in `message.content`
                                  - deepseek: puts thoughts in `message.reasoning_content` (except in streaming mode, which behaves as `none`)
                                  - deepseek-legacy: keeps `<think>` tags in `message.content` while also populating `message.reasoning_content`
                                  (default: none)
         --chat-template-kwargs JSON
                                  sets additional params for the json template parser
         --reasoning-budget N     controls the amount of thinking allowed.
                                  currently only one of: -1 for unrestricted thinking budget, or 0 to disable thinking(default: -1)
         --reasoning-tokens FORMAT
                                  exclude reasoning tokens to select the slot more accurately.
                                  none: include all tokens
                                  auto: exclude all tokens between <think> and </think>
                                  Or comma separated start and end tokens such as [THINK],[/THINK]
                                  (default: auto)
         --no-prefill-assistant   whether to prefill the assistant's response if the last message is an assistant message (default: prefill enabled)
                                  when this flag is set, if the last message is an assistant message then it will be treated as a full message and not prefilled


grammar:

         --grammar GRAMMAR        BNF-like grammar to constrain generations (see samples in grammars/ dir) (default: '')
         --grammar-file FNAME     file to read grammar from
  -j,    --json-schema SCHEMA     JSON schema to constrain generations (https://json-schema.org/), e.g. `{}` for any JSON object
                                  For schemas w/ external $refs, use --grammar + example/json_schema_to_grammar.py instead

embedding:

         --pooling {none,mean,cls,last}
                                  pooling type for embeddings, use model default if unspecified
         --attention {causal,non-causal}
                                  attention type for embeddings, use model default if unspecified

context hacking:

         --rope-scaling {none,linear,yarn}
                                  RoPE frequency scaling method, defaults to linear unless specified by the model
         --rope-scale N           RoPE context scaling factor, expands context by a factor of N
         --rope-freq-base N       RoPE base frequency, used by NTK-aware scaling (default: loaded from model)
         --rope-freq-scale N      RoPE frequency scaling factor, expands context by a factor of 1/N
         --yarn-orig-ctx N        YaRN: original context size of model (default: 0 = model training context size)
         --yarn-ext-factor N      YaRN: extrapolation mix factor (default: -1.0, 0.0 = full interpolation)
         --yarn-attn-factor N     YaRN: scale sqrt(t) or attention magnitude (default: -1.0)
         --yarn-beta-slow N       YaRN: high correction dim or alpha (default: -1.0)
         --yarn-beta-fast N       YaRN: low correction dim or beta (default: -1.0)
  -gan,  --grp-attn-n N           group-attention factor (default: 1)
  -gaw,  --grp-attn-w N           group-attention width (default: 512.0)
  -dkvc, --dump-kv-cache          verbose print of the KV cache
  -nkvo, --no-kv-offload          disable KV offload
  -ctk,  --cache-type-k TYPE      KV cache data type for K (default: f16)
  -ctv,  --cache-type-v TYPE      KV cache data type for V (default: f16)
  -ctkd, --cache-type-k-draft TYPE
                                  KV cache data type for K for the draft model
  -ctvd, --cache-type-v-draft TYPE
                                  KV cache data type for V for the draft model

perplexity:

         --all-logits             return logits for all tokens in the batch (default: false)
         --hellaswag              compute HellaSwag score over random tasks from datafile supplied with -f
         --hellaswag-tasks N      number of tasks to use when computing the HellaSwag score (default: 400)
         --winogrande             compute Winogrande score over random tasks from datafile supplied with -f
         --winogrande-tasks N     number of tasks to use when computing the Winogrande score (default: 0)
         --multiple-choice        compute multiple choice score over random tasks from datafile supplied with -f
         --multiple-choice-tasks N
                                  number of tasks to use when computing the multiple choice score (default: 0)
         --kl-divergence          computes KL-divergence to logits provided via --kl-divergence-base
         --ppl-stride N           stride for perplexity calculation (default: 0)
         --ppl-output-type {0,1}  output type for perplexity calculation (default: 0)

parallel:

  -dt,   --defrag-thold N         KV cache defragmentation threshold (default: -1.0, < 0 - disabled)
  -mea,  --max-extra-alloc        Max extra VRAM allocation per GPU (default: 256)
  -np,   --parallel N             number of parallel sequences to decode (default: 1)
  -ns,   --sequences N            number of sequences to decode (default: 1)
  -cb,   --cont-batching          enable continuous batching (a.k.a dynamic batching) (default: enabled)
  -nocb, --no-cont-batching       disable continuous batching

multi-modality:

         --mmproj FILE            path to a multimodal projector file for LLaVA. see examples/llava/README.md
         --image FILE             path to an image file. use with multimodal models. Specify multiple times for batching
         --image-min-tokens N     minimum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)
         --image-max-tokens N     maximum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)
         --mtmd-kq-type TYPE      data type for multimodality K*Q (default: f32)
         --no-context-shift       disable context-shift.
  --context-shift (auto|on|off|0|1)
                                  set context-shift (default: on)

backend:

         --rpc SERVERS            comma separated list of RPC servers
  -cuda, --cuda-params            comma separate list of cuda parameters
  -draft, --draft-params          comma separate list of draft model parameters
         --mlock                  force system to keep model in RAM rather than swapping or compressing
         --no-mmap                do not memory-map model (slower load but may reduce pageouts if not using mlock)
         --run-time-repack        repack tensors if interleaved variant is available
         --cpu-moe                keep all MoE weights in CPU memory
         --n-cpu-moe N            keep MoE weights of the first N layers in CPU memory
         --fit-margin N           safety margin in MiB when auto-fitting model offloading
  -wgt, --worst-graph-tokens N    number of tokens to use for worst-case graph
         --fit                    automatically determine which tensors to offload to the GPU(s)
         --numa TYPE              attempt optimizations that help on some NUMA systems
                                    - distribute: spread execution evenly over all nodes
                                    - isolate: only spawn threads on CPUs on the node that execution started on
                                    - numactl: use the CPU map provided by numactl
                                  if run without this previously, it is recommended to drop the system page cache before using this
                                  see https://github.com/ggerganov/llama.cpp/issues/1437
  -ngl,  --gpu-layers N           number of layers to store in VRAM
  -ngld, --gpu-layers-draft N     number of layers to store in VRAM for the draft model
  -sm,   --split-mode SPLIT_MODE  how to split the model across multiple GPUs, one of:
                                    - none: use one GPU only
                                    - graph: split model tensors and computation graph across GPUs
                                    - layer (default): split layers and KV across GPUs

  -ts,   --tensor-split SPLIT     fraction of the model to offload to each GPU, comma-separated list of proportions, e.g. 3,1
  -dev,   --device dev1,dev2      comma-separated list of devices to use for offloading (none = don't offload)
                                  Example: CUDA0,CUDA1,RPC[192.168.0.1:8080]

  -devd,   --device-draft dev1,dev2
                                  comma-separated list of devices to use for offloading for the draft model (none = don't offload)
                                  Example: CUDA0,CUDA1,RPC[192.168.0.1:8080]

  -mg,   --main-gpu i             the GPU to use for the model (with split-mode = none),
                                  or for intermediate results and KV (with split-mode = row) (default: 0)
  --max-gpu i                     max. number of GPUs to use at a time with split mode 'graph', (default: 0)

model:

         --check-tensors          check model tensor data for invalid values (default: false)
         --override-kv KEY=TYPE:VALUE
                                  advanced option to override model metadata by key. may be specified multiple times.
                                  types: int, float, bool, str. example: --override-kv tokenizer.ggml.add_bos_token=bool:false
         --lora FNAME             apply LoRA adapter (can be repeated to use multiple adapters)
         --lora-scaled FNAME S    apply LoRA adapter with user defined scaling S (can be repeated to use multiple adapters)
         --control-vector FNAME   add a control vector
                                  note: this argument can be repeated to add multiple control vectors
         --control-vector-scaled FNAME SCALE
                                  add a control vector with user defined scaling SCALE
                                  note: this argument can be repeated to add multiple scaled control vectors
         --control-vector-layer-range START END
                                  layer range to apply the control vector(s) to, start and end inclusive
  -m,    --model FNAME            model path (default: models/$filename with filename from --hf-file
                                  or --model-url if set, otherwise models/7B/ggml-model-f16.gguf)
  -md,   --model-draft FNAME      draft model for speculative decoding (default: unused)
  -mu,   --model-url MODEL_URL    model download url (default: unused)
  -hfr,  --hf-repo REPO           Hugging Face model repository (default: unused)
  -hff,  --hf-file FILE           Hugging Face model file (default: unused)
  -hft,  --hf-token TOKEN         Hugging Face access token (default: value from HF_TOKEN environment variable)
  -mtp, --multi-token-prediction  whether to use multi-token-prediction (if supported) (default: false)
  -no-mtp, --no-multi-token-prediction
                                  whether to use multi-token-prediction (if supported) (default: true)
  --draft-max, --draft, --draft-n N
                                  number of tokens to draft for speculative decoding (default: 16)
  --draft-min, --draft-n-min N    minimum number of draft tokens to use for speculative decoding
  --draft-p-min P                 minimum speculative decoding probability (greedy) (default: 0.8)
  --spec-type Name [none | ngram - cache | ngram - simple | ngram - map - k | ngram - map - k4v | ngram - mod]
                                  type of speculative decoding to use when no draft model is provided (default: 0)

  --spec-ngram-size-n N           ngram size N for ngram-simple/ngram-map speculative decoding, length of lookup n-gram (default: 12)

  --spec-ngram-size-m N           ngram size M for ngram-simple/ngram-map speculative decoding, length of draft m-gram (default: 48)

  --spec-ngram-min-hits N         minimum hits for ngram-map speculative decoding (default: 1)


retrieval:

         --context-file FNAME     file to load context from (repeat to specify multiple files)
         --chunk-size N           minimum length of embedded text chunks (default: 64)
         --chunk-separator STRING
                                  separator between chunks (default: '
                                  ')

passkey:

         --junk N                 number of times to repeat the junk text (default: 250)
         --pos N                  position of the passkey in the junk text (default: -1)

imatrix:

  -o,    --output FNAME           output file (default: 'imatrix.dat')
         --output-frequency N     output the imatrix every N iterations (default: 10)
         --save-frequency N       save an imatrix copy every N iterations (default: 0)
         --process-output         collect data for the output tensor (default: false)
         --no-ppl                 do not compute perplexity (default: true)
         --chunk N                start processing the input from chunk N (default: 0)

bench:

  -pps                            is the prompt shared across parallel sequences (default: false)
  -npp n0,n1,...                  number of prompt tokens
  -ntg n0,n1,...                  number of text generation tokens
  -npl n0,n1,...                  number of parallel prompts

embedding:

         --embd-normalize         normalisation for embendings (default: 2) (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)
         --embd-output-format     empty = default, "array" = [[],[]...], "json" = openai style, "json+" = same "json" + cosine similarity matrix
         --embd-separator         separator of embendings (default \n) for example "<#sep#>"

server:

         --host HOST              ip address to listen (default: 127.0.0.1)
         --port PORT              port to listen (default: 8080)
         --path PATH              path to serve static files from (default: )
         --embedding(s)           restrict to only support embedding use case; use only with dedicated embedding models (default: disabled)
         --webui NAME             controls which webui to server:
                                  - none: disable webui
                                  - auto: default webui
                                  - llamacpp: llamacpp webui
                                  (default: auto)
         --api-key KEY            API key to use for authentication (default: none)
         --api-key-file FNAME     path to file containing API keys (default: none)
         --ssl-key-file FNAME     path to file a PEM-encoded SSL private key
         --ssl-cert-file FNAME    path to file a PEM-encoded SSL certificate
         --timeout N              server read/write timeout in seconds (default: 600)
         --threads-http N         number of threads used to process HTTP requests (default: -1)
         --system-prompt-file FNAME
                                  set a file to load a system prompt (initial prompt of all slots), this is useful for chat applications
         --log-format {text,json}
                                  log output format: json or text (default: json)
         --metrics                enable prometheus compatible metrics endpoint (default: disabled)
         --no-slots               disables slots monitoring endpoint (default: enabled)
         --slot-save-path PATH    path to save slot kv cache (default: disabled)
         --chat-template JINJA_TEMPLATE
                                  set custom jinja chat template (default: template taken from model's metadata)
                                  only commonly used templates are accepted:
                                  https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template
  -sps,  --slot-prompt-similarity SIMILARITY
                                  how much the prompt of a request must match the prompt of a slot in order to use that slot (default: 0.10, 0.0 = disabled)

         --lora-init-without-apply
                                  load LoRA adapters without applying them (apply later via POST /lora-adapters) (default: disabled)

logging:

         --simple-io              use basic IO for better compatibility in subprocesses and limited consoles
  -ld,   --logdir LOGDIR          path under which to save YAML logs (no logging if unset)
         --log-test               Run simple logging test
         --log-disable            Disable trace logs
         --log-enable             Enable trace logs
         --log-file FNAME         Specify a log filename (without extension)
         --log-new                Create a separate new log file on start. Each log file will have unique name: "<name>.<ID>.log"
         --log-append             Don't truncate the old log file.

cvector:

  -o,    --output FNAME           output file (default: 'control_vector.gguf')
         --positive-file FNAME    positive prompts file, one prompt per line (default: 'examples/cvector-generator/positive.txt')
         --negative-file FNAME    negative prompts file, one prompt per line (default: 'examples/cvector-generator/negative.txt')
         --pca-batch N            batch size used for PCA. Larger batch runs faster, but uses more memory (default: 100)
         --pca-iter N             number of iterations used for PCA (default: 1000)
         --method {pca,mean}      dimensionality reduction method to be used (default: pca)

export-lora:

  -m,    --model                  model path from which to load base model (default '')
         --lora FNAME             path to LoRA adapter  (can be repeated to use multiple adapters)
         --lora-scaled FNAME S    path to LoRA adapter with user defined scaling S  (can be repeated to use multiple adapters)
  -t,    --threads N              number of threads to use during computation (default: 8)
  -o,    --output FNAME           output file (default: 'ggml-lora-merged-f16.gguf')

11:19:30-846856 ERROR    Error loading the model with llama.cpp: Server process terminated unexpectedly with exit code:
                         1

Win 10 pro
CPU Threadripper 1900X
GPU x4 2080TI 22gb each
RAM 64
SSD

Win 10 pro
CPU Threadripper 1900X
GPU x4 3090 24gb each
RAM 64
SSD