# kromoss-image: an image model inside a capsule.## What this example adds to model-for-opencode:#   - the image.generate kind: m64's front lets POST /v1/images/generations#     through, and only `prompt` and `seed` in its body;#   - [params]: the settings the server bakes in, published so callers (and the#     site) can see them; a caller may send the same value, never another;#   - [routes] extra: one more path, /v1/config, that the front lets through;#   - a Dockerfile on NVIDIA's PyTorch image, with every pip package pinned.schema = "m64/capsule@1"description = "An image model in a capsule: Kromoss with its 8-step DMD2 LoRA on diffusers, text to 1024x1024 PNG in about 19 s on a GB10. Shows the image.generate kind, [[artifacts]] for 40 GB of weights, [params] and an extra route."kinds = ["image.generate"]authors = ["motif42"]license = "mit"[hardware]# Built and measured on an NVIDIA GB10 (DGX Spark class, ARM). The base image is# also built for x86_64; on a big x86 card set platform and gpu to match it.platform = "linux-aarch64"gpu = "NVIDIA GB10"gpu_count = 1# ~10 GB transformer + ~17 GB Qwen3.5-9B text encoder (bf16) + fp32 VAE and LoRA.# On unified memory (GB10) m64 adds ram_gb to this; here it is all in vram_gb.vram_gb = 40driver = ">=580"disk_gb = 40[runtime]sandbox = "container"# No image: m64 builds the Dockerfile (nvcr.io/nvidia/pytorch pinned by digest).gpu = true# PyTorch's data loaders and CUDA IPC use shared memory: give it more than the 1 GB default.shm_gb = 8internal_port = 9219health = "/health"# Reading ~40 GB of weights and moving them to the GPU takes minutes.expected_load_seconds = 420model_name = "kromoss-dmd2"user = "65534:65534"# The weights: one Hugging Face repo at a fixed commit, only the files the# diffusers pipeline needs (the repo also has ComfyUI repackings and card images).# m64 downloads them on the first serve (or `m64 install`), verifies them, and# mounts them read-only at /weights/kromoss. With models_dir set# (`m64 config set models_dir /mnt/models`), they live there, shared by capsules.[[artifacts]]type = "hf"repo = "lodestones/Kromoss"revision = "7f9bb7b06d7b6c27d294b0bab5a2b3056c379279"include = [  ".gitattributes", "LICENSE", "README.md", "model_index.json", "*.py",  "8-steps-*.safetensors",  "scheduler/*", "text_encoder/*", "tokenizer/*", "transformer/*", "vae/*",]mount = "/weights/kromoss"# Baked into kromoss_server.py; returned as `params_used` with every image.[params]size = "1024x1024"num_inference_steps = 8guidance_scale = 1.0shift = 5.0lora = "8-steps-dmd2-lora"# /v1/config describes the fixed settings and the accepted fields. The front# lets it through; every other path that isn't a kind route is a 404.[routes]extra = ["/v1/config"]