AI Changelog Aggregator

vocab : add Carbon-3B (HybridDNATokenizer) support (#23410)

vocab : add Carbon-3B (HybridDNATokenizer) support

Adds a new BPE pre-type LLAMA_VOCAB_PRE_TYPE_CARBON for the HybridDNATokenizer used by HuggingFaceBio/Carbon-{500M,3B,8B}. The base BPE is Qwen3-4B-Base's; what differs is that text inside ... regions is chunked into fixed 6-mers (right-padded with 'A' on the trailing partial), and any base outside ACGT maps to .

src/llama-vocab.{h,cpp}: new pre-type, dispatched from llm_tokenizer_bpe_session::tokenize.
src/llama-vocab-carbon.h: pure helpers (tokenize_carbon, emit_dna_kmers) factored out for unit testing — no llama_vocab dependency, vocab access goes through a std::function.
conversion/base.py: detect HybridDNATokenizer by class name in get_vocab_base_pre (chktxt collides with Qwen3 base since it has no ), and pass trust_remote_code=True in get_vocab_base so the custom tokenizer class can load.
tests/test-tokenizer-carbon.cpp: 12 cases covering single 6-mer, multi 6-mer, lowercase, invalid base -> , partial k-mer right-pad, mixed text+DNA, empty , unterminated , two regions, vocab miss.
vocab : align Carbon-3B changes with llama.cpp conventions
Fold tokenize_carbon + emit_dna_kmers inline into llm_tokenizer_bpe_session (drop src/llama-vocab-carbon.h), matching how every other tokenizer keeps its helpers inside llama-vocab.cpp.
Replace the standalone unit test with the conventional test-tokenizer-0 row backed by models/ggml-vocab-carbon.gguf (vocab-only conversion) + .inp/.out fixtures covering single 6-mer, multi 6-mer, lowercase, invalid base -> , partial right-pad, mixed text+DNA, empty , unterminated , two regions.
Register "carbon" in convert_hf_to_gguf_update.py's model list (pointing at HuggingFaceBio/Carbon-3B) and teach both AutoTokenizer call sites in the updater to pass trust_remote_code=True for it, matching how t5 is special-cased.
vocab : move Carbon dispatch to _set_vocab_carbon + LlamaModel branch

Refactor the conversion-side changes to follow the per-tokenizer-family convention used by _set_vocab_qwen, _set_vocab_interns1, _set_vocab_glm, etc. instead of conditionalising the shared get_vocab_base / get_vocab_base_pre paths.

conversion/base.py: add _set_vocab_carbon — self-contained, loads with trust_remote_code=True so HybridDNATokenizer's merged Qwen3 + DNA vocab is visible, writes tokenizer.ggml.pre = "carbon" directly.
conversion/llama.py: branch in LlamaModel.set_vocab on tokenizer_config.json["tokenizer_class"] == "HybridDNATokenizer" and dispatch to _set_vocab_carbon. Same precedent as conversion/bert.py (tokenizer_class branch between BertTokenizer / RobertaTokenizer) and conversion/phi.py.
conversion/base.py: revert the conditional in get_vocab_base and the class-name short-circuit in the auto-generated get_vocab_base_pre.
tests : expand ggml-vocab-carbon.gguf fixtures with model-card examples

Add 6 cases from the Carbon-3B model card on top of the existing edge coverage: the unterminated basic-completion prompt, the closed 33-bp example, the metadata-conditioned prompt (with and which BPE-decompose since they are not in the vocab), the documented anti-pattern of raw DNA without tags, and the two likelihood-scoring examples. Brings the suite to 19 cases.

vocab : promote HybridDNATokenizer to its own LLAMA_VOCAB_TYPE

Refactor per upstream review:

This should be its own tokenizer model, ie. carbonhybriddna instead of gpt2 and not carbon pre-tokenizer. That way you can keep the correct pre-tokenizer, in case that ever changes.

Previously the tokenizer was modelled as LLAMA_VOCAB_TYPE_BPE plus a new LLAMA_VOCAB_PRE_TYPE_CARBON, which (a) put a CARBON-specific branch inside llm_tokenizer_bpe_session::tokenize (only existing pre-types differ in regex, not dispatch logic), and (b) conflated "hybrid DNA tokenization" with "Qwen3 BPE pre-tokenizer".

This change moves it to its own vocab type, peer to PLAMO2, with the GGUF model name matching the HF tokenizer class (HybridDNATokenizer):

include/llama.h: new LLAMA_VOCAB_TYPE_HYBRIDDNA = 7.
src/llama-vocab.cpp: new llm_tokenizer_hybriddna + session that owns std::unique_ptr for non- text and routes raw text through a DNA-aware splitter; wired into init_tokenizer, tokenize, type_name, byte_to_token, and the BPE-style token_to_piece case (DNA k-mers + // are pure ASCII, so byte-level BPE decoding handles them). LLAMA_VOCAB_TYPE_HYBRIDDNA gets its own branch in the vocab-type config block alongside SPM/WPM/UGM/RWKV, where pre_type is set to QWEN2 and the matching add_space_prefix / escape_whitespaces / clean_spaces flags are applied — mirroring qwen2's BPE path so byte-level BPE merging stays bit-identical to the Python reference for non-DNA text.
src/llama-vocab.h: drop the short-lived LLAMA_VOCAB_PRE_TYPE_CARBON.
conversion/base.py: _set_vocab_hybriddna writes tokenizer.ggml.model = "hybriddna" (no separate pre).
conversion/llama.py: dispatch on tokenizer_class == "HybridDNATokenizer" same as bert.py / phi.py do.
models/ggml-vocab-hybriddna.gguf{,.inp,.out}: renamed fixture + regenerated metadata.
convert_hf_to_gguf_update.py: drop the stale chkhsh entry and trust_remote_code special-case (no longer needed since dispatch is now class-name driven, not chkhsh).

Verified end-to-end against HuggingFaceBio/Carbon-{500M,3B,8B}: tokenization is bit-identical to the Python HybridDNATokenizer for all 19 test fixtures plus the model-card metadata-conditioned prompt; greedy completion produces the same DNA continuation as the Python reference; spec-dec with 500M as draft for 8B still works.

vocab : relax llm_tokenizer_bpe assert to allow HYBRIDDNA
vocab : drop llm_tokenizer_bpe vocab-type assert
vocab : write tokenizer.ggml.pre for HYBRIDDNA, share BPE dispatch
vocab : assert BPE or HYBRIDDNA in llm_tokenizer_bpe
vocab : annotate #endif with PRETOKENIZERDEBUG
vocab : drop local hybriddna fixture (moves to ggml-org/vocabs)
deduplicate
simplify
simplify

Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@scala.com

macOS/iOS:

Linux:

Android:

Android arm64 (CPU)

Windows:

openEuler: