Carbon-3B GGUF
Running with llama.cpp
Carbon is a base DNA model (not instruction-tuned). Use the raw completion
front-end so llama.cpp does not apply any chat templating:
If you use llama-cli instead, pass -no-cnv so it does not wrap the prompt
in assistant-style markers (otherwise the model may emit annotation tags such
as <protein_coding_region> instead of DNA).
Available files
K-quants are produced with --token-embedding-type Q8_0 --output-tensor-type Q8_0
so the sensitive embedding/output tensors stay at Q8_0 precision (important for
this model's tight DNA-vs-text logit margins).
Requires a recent llama.cpp
HybridDNATokenizer support was merged in ggml-org/llama.cpp#23410, so any build from master after that works:
Usage
Download
Basic DNA completion
Metadata-conditioned generation
Speculative decoding with Carbon-500M draft (~1.35x speedup)
Carbon-500M shares the HybridDNA vocab, so it works as a drop-in draft model. Grab it first:
Then run the standalone tool with --model-draft:
Or serve the 3B with the 500M draft (llama-server accepts the same -md flag):
Likelihood scoring
The source card's Python score() function computes mean log-prob per DNA token. In llama.cpp the closest tools are llama-perplexity for corpus-level perplexity (perplexity = exp(-mean_logprob)):
Or llama-server with logprobs for per-token log-probabilities:
Long context with YaRN (65k tokens ≈ 393 kbp)
Mirrors the source card's rope_scaling = {type: yarn, factor: 4.0, original_max_position_embeddings: 32768}:
Base-pair-level generation (FNS branch) — not supported
The revision="fns" example from the source card needs custom modeling code (factorized nucleotide supervision head), which only the Python transformers path can load. llama.cpp can't run that branch.
Tokenization parity
llama.cpp produces byte-for-byte identical token IDs to the Python HybridDNATokenizer (loaded with trust_remote_code=True) on the standard <dna>/metadata/edge-case fixtures shipped in ggml-org/vocabs.
See also
License
Apache-2.0, inherited from the source model.