| --- |
| license: mit |
| tags: |
| - biology |
| - mrna design |
| - codon optimization |
| pipeline_tag: translation |
| --- |
| |
| # Trias-Small: a mammalian variant of Trias for codon generation |
|
|
| Trias-Small is a variant of [**Trias**](https://huggingface.co/lareaulab/Trias), |
| the encoder-decoder model that reverse-translates protein sequences into codon |
| sequences. Unlike Trias, which was trained on vertebrate mRNA sequences across |
| many species, **Trias-Small was trained only on mammalian coding sequences**. |
|
|
| For full setup, decoding options (greedy / beam search), and citation, see the |
| main [**lareaulab/Trias**](https://huggingface.co/lareaulab/Trias) model card. |
| This card only documents what differs. |
|
|
| ## Key difference from Trias |
|
|
| Trias-Small is trained only on mammalian sequences and does not take an input |
| species tag — there is no `>>{species}<<` prefix. |
|
|
| ## Reverse Translation |
|
|
| Trias-Small uses the custom `TriasTokenizer`, so the `trias` package must be |
| installed: |
|
|
| ```bash |
| pip install git+https://github.com/lareaulab/Trias.git |
| ``` |
|
|
| ```python |
| import torch |
| from huggingface_hub import hf_hub_download |
| from transformers import BartForConditionalGeneration |
| from trias.tokenizer import TriasTokenizer |
| |
| repo = "lareaulab/Trias-Small" |
| |
| # The tokenizer is built directly from the vocab file |
| vocab_file = hf_hub_download(repo, "vocab.json") |
| tokenizer = TriasTokenizer(vocab_file, separate_vocabs=False, model_max_length=2048) |
| model = BartForConditionalGeneration.from_pretrained(repo).eval() |
| |
| # No species tag — just the protein sequence (end with '*' for the stop) |
| protein_sequence = "MTEITAAMVKELRESTGAGMMDCKNALSETQ*" |
| |
| input_ids = tokenizer.encode(protein_sequence, return_tensors="pt") |
| outputs = model.generate(input_ids, max_length=tokenizer.model_max_length) |
| codon_sequence = tokenizer.decode(outputs[0], skip_special_tokens=True) |
| |
| print("Codon sequence:", codon_sequence) |
| ``` |
|
|
| Beam search works the same way as in the main Trias model (pass `num_beams=...` |
| to `model.generate`). |
|
|
