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
<dna>...</dna> regions is chunked into fixed 6-mers (right-padded
with 'A' on the trailing partial), and any base outside ACGT maps
to <oov>.
* 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 <dna>), 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 -> <oov>, partial k-mer
right-pad, mixed text+DNA, empty <dna></dna>, unterminated <dna>,
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 -> <oov>, partial
right-pad, mixed text+DNA, empty <dna></dna>, unterminated <dna>,
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 <vertebrate_mammalian>
and <protein_coding_region> which BPE-decompose since they are not in
the vocab), the documented anti-pattern of raw DNA without <dna> 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<llm_tokenizer_bpe> for non-<dna> 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 + <dna>/</dna>/<oov>
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>
