Load a model via REST API

Load a model via REST API

Usage

lms_load(
  model,
  context_length = NULL,
  eval_batch_size = NULL,
  flash_attention = NULL,
  num_experts = NULL,
  offload_kv_cache_to_gpu = NULL,
  echo_load_config = FALSE,
  force = FALSE,
  host = "http://localhost:1234",
  ...
)

Arguments

model

Character. Unique identifier for the model to load.

context_length

Integer. Maximum number of tokens that the model will consider.

eval_batch_size

Integer. Number of input tokens to process together in a single batch during evaluation.

flash_attention

Logical. Whether to optimize attention computation.

num_experts

Integer. Number of experts to use during inference for MoE models.

offload_kv_cache_to_gpu

Logical. Whether KV cache is offloaded to GPU memory.

echo_load_config

Logical. If TRUE, echoes the final load configuration in the response.

force

Logical. If TRUE, bypasses the check for currently loaded models and requests a new instance from the server. Note that this does not overwrite or replace the existing model; it loads a second concurrent instance into VRAM. Defaults to FALSE.

host

Character. The host address of the local server. Defaults to "http://localhost:1234".

...

Additional arguments passed to the API request body (useful for future API parameters).

Value

Invisibly returns the model identifier string on success, or the load configuration list if echo_load_config = TRUE.

See also

LM Studio Load Model API

Examples

if (FALSE) { # \dontrun{
lms_server_start()
lms_download("google/gemma-3-1b")

# Load a model with default settings
lms_load("google/gemma-3-1b")

# Load a model with custom context length and flash attention enabled
lms_load("google/gemma-3-1b", context_length = 8192, flash_attention = TRUE)
} # }