ggml-org/llama.cpp b11454 on GitHub

Details

model : add K2 Horizon dense and MoVA support (#29535)

model: K2 Horizon gguf conversion code
model: loading hparams and tensors in k2-horizon.cpp
model: K2 Horizon compute graph
model: K2 Horizon compute graph adjustment and registering tokenizers
model: K2 Horizon chat template and accomodate safetensors naming
unicode : add the K2-Horizon pre-tokenizer splitter

The K2-Horizon regex had no arm in unicode_regex_split_custom and fell through to the
general std::regex fallback, which fails two ways.

On MSVC std::regex rejects \p{...}, so no K2-Horizon GGUF loads on Windows at all:
llama-quantize, llama-imatrix and llama-perplexity all abort with
regex_error(error_escape) before a token is produced.

Where the fallback does compile it is still wrong. unicode_regex_split collapses each
codepoint to a single byte naming its Unicode category before matching, and U+200C/U+200D
are category Control, which has no entry in k_ucat_cpt, so both become the 0xD0 fallback
byte. The literal ‌ and ‍ alternatives in K2's regex can then never match and
every ZWNJ or ZWJ ends a letter run.

The splitter is the existing llama3 one with a single rule widened, since K2's regex
differs from llama3's only in that a letter run also takes marks, ZWNJ and ZWJ.

tests/test-unicode.cpp gains a case for this: it fails before the change with
[Amy] [ZWNJ khaham] and passes after with the run intact.

tests: expand K2 Horizon unicode splitter coverage
unicode: handle K2 Horizon case folding and empty input

Assisted-by: Codex

jinja : support sequence indices in selectattr and rejectattr

Assisted-by: Codex

model : add K2 Horizon dense and MoVA support

Includes the K2 Horizon implementation from ifm-ai/llama.cpp with converter, tensor-parallel and model save/reload fixes.

Assisted-by: Codex

chat : support K2 Horizon reasoning and tool calls

Assisted-by: Codex

conversion: remove obsolete K2 Aurora alias

Assisted-by: Codex

k2-horizon: enforce response schemas and load YaRN betas

Constrain final JSON after reasoning, accept flexible JSON tool envelopes,
enforce XML dialects, and handle repeated or alternate thinking markers.
Load YaRN beta metadata instead of retaining the default values.

Add schema, streaming, continuation, and model reload regressions. Validate
CUDA and CPU builds and 0.9B, 4B, and MoVA conversation/tool round trips.

Assisted-by: Codex