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dna-bolinas-scaling-v0.5-h896-p128M-43ec40, with its tokenizer bundled. It accompanies A 1B standard Transformer rivals Evo 2 40B on variant effect prediction.| Field | Value |
|---|---|
| Architecture | Qwen3-compatible decoder-only Transformer |
| Parameters | 128,484,480 |
| Layers | 10 |
| Hidden / intermediate size | 896 / 3,584 |
| Attention heads / KV heads | 7 / 7 |
| Context | 256 tokens: one BOS token followed by up to 255 DNA bases |
| Checkpoint | Final checkpoint, step 215573 (after 215,574 zero-indexed training steps) |
| Token exposure | approximately 84.77B nucleotide tokens |
| Stored weight dtype | float32 |
| License | Apache-2.0 |
gs://marin-us-east5/checkpoints/dna-bolinas-scaling-v0.5-h896-p128M-43ec40/hf/step-215573; the byte-identical evals_v2 transfer cache is s3://oa-bolinas/snakemake/analysis/evals_v2/results/checkpoints/scaling-v0.5-h896-p128M-step-215573. The commit-pinned training script defines the production ladder.1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3repo_id = "marin-dna/marin-dna-scaling-v0.5-h896-p128M"
4tokenizer = AutoTokenizer.from_pretrained(repo_id)
5model = AutoModelForCausalLM.from_pretrained(repo_id)[PAD]=0, [UNK]=1, [BOS]=2, a=3, c=4, g=5, t=6. Pass raw DNA strings containing A, C, G, and T without spaces. The tokenizer lowercases input and prepends [BOS]; it has no EOS token. Other symbols map to [UNK]. Because BOS occupies one of the 256 positions, inputs are limited to 255 DNA bases.