LORA_APPLY_MODE         LoRA apply modes
PREDICTION              Prediction types
PREVIEW                 Preview decode modes
RNG_TYPE                RNG types
SAMPLE_METHOD           Sampling methods
SCHEDULER               Schedulers
SD_CACHE_MODE           Cache modes
SD_TYPE                 Weight types (ggml quantization types)
sd_api_start            Start sd2R REST API server
sd_api_stop             Stop sd2R REST API server
sd_app                  Launch sd2R Shiny GUI
sd_cache_params         Create cache configuration for step caching
sd_convert              Convert model to different quantization format
sd_ctx                  Create a Stable Diffusion context
sd_decode_latent        Decode a latent into a pixel image (low-level
                        VAE decode)
sd_default_params       Default generation parameters
sd_denoise_step         Run a single denoise step (low-level)
sd_destroy_context      Release a stable diffusion context and free its
                        VRAM
sd_download_model       Download a Stable Diffusion model from Kaggle
                        Models
sd_encode_image         Encode an image into a latent (low-level VAE
                        encode)
sd_encode_text          Encode a text prompt into conditioning
                        (low-level)
sd_generate             Generate images (unified entry point)
sd_generate_multi_gpu   Parallel generation across multiple GPUs
sd_generate_multiref    Generate an image conditioned on multiple
                        reference images
sd_image_to_array       Convert SD image to R numeric array
sd_img2img              Generate images with img2img
sd_inverse_noise_scale
                        Undo final-step latent scaling (low-level)
sd_list_models          List registered models
sd_load_image           Load image from file as SD image
sd_load_mask            Load a mask from a PNG file as a 1-channel SD
                        image
sd_load_model           Load a registered model
sd_load_pipeline        Load pipeline from JSON
sd_node                 Create a pipeline node
sd_noise_scale          Scale noise into the starting latent
                        (low-level)
sd_pipeline             Create a pipeline from nodes
sd_preview_start        Enable live generation previews
sd_preview_stop         Disable live generation previews
sd_profile_get          Get raw profile events
sd_profile_start        Start profiling
sd_profile_stop         Stop profiling
sd_profile_summary      Build a profile summary from raw events
sd_read_preview         Read the current preview frame
sd_register_model       Register a model in the sd2R model registry
sd_remove_model         Remove a model from the registry
sd_run_pipeline         Run a pipeline
sd_sample               Run the sampling loop (low-level)
sd_sample_stepwise      Run the sampling loop step-by-step in R
                        (low-level)
sd_sampler_begin        Open / close a step-wise sampling window
                        (low-level)
sd_sampler_sigmas       Sigma schedule for a sampler (low-level)
sd_save_image           Save SD image to PNG file
sd_save_pipeline        Save pipeline to JSON
sd_scan_models          Scan a directory for models and register them
sd_supports_ref_images
                        Does the loaded model support reference images?
sd_system_info          Get system information
sd_txt2img              Generate images from text prompt
sd_txt2img_highres      High-resolution image generation via
                        patch-based pipeline
sd_txt2img_tiled        Tiled diffusion sampling (MultiDiffusion)
sd_unload_all           Unload all models from memory
sd_unload_model         Unload a model from memory
sd_upscale_image        Upscale an image using ESRGAN
sd_vulkan_device_count
                        Get number of Vulkan GPU devices
