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Config

helical.models.helix_mrna.HelixmRNAConfig

HelixmRNAConfig class to store the configuration of the Helix-mRNA model.

Parameters:

Name Type Description Default
batch_size int

The batch size

 10
device str

The device to use. Accepts any string torch.device accepts, e.g. "cpu", "cuda", "cuda:0".

 "cpu"
max_length int

The maximum length of the input sequence.

 12288
nproc int

Number of processes to use for data processing.

 1
output_attentions bool

Whether to return attention weights from get_embeddings. Must be set at construction time: True forces eager attention (required for attention output), False uses flash_attention_2 when available, else sdpa. Note: eager attention materialises the full O(seq²) matrix and may OOM on long sequences or large batches.

 False
Source code in helical/models/helix_mrna/helix_mrna_config.py 
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class HelixmRNAConfig:
    """HelixmRNAConfig class to store the configuration of the Helix-mRNA model.

    Parameters
    ----------
    batch_size : int, optional, default=10
        The batch size
    device : str, optional, default="cpu"
        The device to use. Accepts any string torch.device accepts, e.g. "cpu",
        "cuda", "cuda:0".
    max_length : int, optional, default=12288
        The maximum length of the input sequence.
    nproc: int, optional, default=1
        Number of processes to use for data processing.
    output_attentions : bool, optional, default=False
        Whether to return attention weights from get_embeddings. Must be set at
        construction time: True forces eager attention (required for attention
        output), False uses flash_attention_2 when available, else sdpa. Note:
        eager attention materialises the full O(seq²) matrix and may OOM on long
        sequences or large batches.
    """

    def __init__(
        self,
        batch_size: int = 10,
        device: str = "cpu",
        max_length: int = 12288,
        nproc: int = 1,
        output_attentions: bool = False,
    ):

        model_name: Literal["helical-ai/Helix-mRNA"] = "helical-ai/Helix-mRNA"

        self.config = {
            "model_name": model_name,
            "input_size": max_length,
            "batch_size": batch_size,
            "device": device,
            "nproc": nproc,
            "output_attentions": output_attentions,
        }