kimodo.cpp

GGML/C++ implementation of NVIDIA's Kimodo text-to-motion model.

Status

Kimodo-SMPLX-RP-v1 accepts either a UTF-8 prompt or a precomputed LLM2Vec embedding and generates unconstrained SMPL-X22 local rotations and root translations on CPU or Vulkan. The text encoder uses eight-layer Vulkan chunks by default; set KIMODO_TEXT_LAYER_CHUNK=1..32 to tune VRAM use.

Included: checked GGUF loading, safetensors conversion, DDIM sampling, C/C++ APIs, CPU/Vulkan parity tests, and a local text-to-motion demo. Constraints, SOMA, G1, GLB export, and quantised models are not implemented yet.

Build and test

GGML is a pinned Git submodule:

git submodule update --init --recursive
nix develop path:. --command cmake --preset debug
nix develop path:. --command cmake --build --preset debug
nix develop path:. --command ctest --preset debug

The standard test suite requires the local motion GGUF, text bundle, and fixtures. It never downloads weights by itself. release, asan-ubsan, and fuzz presets are also available.

For sanitizer work:

nix develop path:. --command cmake --preset asan-ubsan
nix develop path:. --command cmake --build --preset asan-ubsan
nix develop path:. --command env \
  LD_LIBRARY_PATH="$PWD/build/asan-ubsan/ggml/src:$PWD/build/asan-ubsan/ggml/src/ggml-vulkan:$LD_LIBRARY_PATH" \
  ASAN_OPTIONS=detect_leaks=0:abort_on_error=1 UBSAN_OPTIONS=print_stacktrace=1 \
  ctest --preset asan-ubsan --output-on-failure

Leak detection is disabled because Vulkan loader/driver allocations are global to the process. The GGUF parser fuzzer requires Clang.

API

include/kimodo/kimodo_capi.h is the C API. Model loading checks the motion GGUF and text bundle before inference. Use kimodo_generate_embedding for 4096 F32 values or kimodo_generate for text. Both return SMPL-X22 root translations and local XYZW rotations.

Demo

After building the debug preset and downloading the native GGUF bundle:

go run ./demo -addr 0.0.0.0:8094

Open http://localhost:8094. The left sidebar contains the prompt and a persistent history; choosing a previous animation restores its prompt for a new generation.

Weights

The ready-to-run native GGUF bundle is published under the Hugging Face LocalAI-io organisation (not GitHub's localai-org). Download it directly; this avoids recreating the conversion locally:

nix develop path:. --command scripts/download_gguf_weights.sh --output "$PWD"

The installer verifies the published manifest and SHA-256 hashes. Use --motion-only when supplying a precomputed 4096-float LLM2Vec embedding.

The GGUF bundle includes converted Meta Llama 3 material and Kimodo is non-commercial research-only. Review the published model card and upstream licences before downloading or redistributing.

Regenerating the bundle

This is only needed to reproduce a conversion. The SMPL-X checkpoint and Llama base model are gated. After accepting their Hugging Face licences and authenticating, download the exact revisions and hash manifests with:

nix develop path:. --command hf auth login
nix develop path:. --command scripts/download_weights.sh \
  --output "$PWD/models" --with-text

Convert the local LLM2Vec model to the native component bundle with:

nix develop path:. --command scripts/convert_llm2vec_bundle.sh \
  "$PWD/models/llama3-8b-instruct-base" "$PWD/generated/llm2vec-text-bundle"

Validate a prospective release without network access, then explicitly upload it from an account allowed to publish to LocalAI-io:

nix develop path:. --command python scripts/publish_gguf.py
nix develop path:. --command python scripts/publish_gguf.py \
  --upload --confirm-upstream-licences