Release v0.5.0 · espetro/dinov2.cpp

Highlights

Added a public C API and libdinov2 target, with opaque model/context handles, batch encoding, and model loading from files, buffers, or callbacks.
Added a WebAssembly SIMD128 build and browser demo, now hosted at https://espetro.github.io/dinov2.cpp/.
Added an optional HTTP embeddings server, plus deduplication, container, and CI visual-regression examples. These remain tier-2, best-effort surfaces.
Fixed inherited inference and loader issues, including flash-attention padding corruption, GGUF validation, backend device-pointer reads, model-load memory leaks, and positional embedding interpolation.
Added backbone-only GGUF conversion and publishing for all eight DINOv2 variants, alongside the eight classifier variants. Backbone models support feature extraction and reject classification.
Added ARM64 benchmark evidence, nightly parity checks, and the JSONL output contract check.
Improved large-image safety, preprocessing modes, batching, binary embeddings metadata, and clean allocation errors from v0.4.0.
Added Joaquin Terrasa's copyright notice while retaining the original upstream copyright notice. The project remains MIT licensed.

The C API is still unstable during the 0.x series. Pin a release when embedding it.
The browser demo uses single-threaded WebAssembly SIMD128. Native CPU performance is faster.
The server and examples are tier-2 and are not production-service guarantees.
DINOv2 is image-only, not a CLIP-style text-image model. Image decoding is limited to the formats supported by stb_image.
Benchmark results are hardware-specific; consult docs/benchmarks.md and docs/parity/ for methodology and measurements.

Release binaries are attached below with SHA256 checksums. GGUF model weights are published separately under https://huggingface.co/dinov2-cpp-core.