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Backbones

modelgenerator.backbones.GenBioBERT

Bases: HFSequenceBackbone

GenBioBERT model

Note

Models using this interface include aido_dna_7b, aido_dna_300m, dna_dummy, aido_dna_debug, aido_rna_1b600m, aido_rna_1b600m_cds, aido_rna_1m_mars, aido_rna_25m_mars, aido_rna_300m_mars, aido_rna_650m, aido_rna_650m_cds.

FSDP auto_wrap_policy is [transformers.models.rnabert.modeling_rnabert.RNABertLayer]

Parameters:

Name Type Description Default
config_overwrites dict

Optional model arguments for PretrainedConfig. Defaults to None.

required
model_init_args dict

Optional model arguments passed to its init method. Defaults to None.

required
from_scratch bool

Whether to create the model from scratch. Defaults to False.

False
max_length int

Maximum sequence length. Defaults to 512.

None
use_peft bool

Whether to use LoRA PEFT. Defaults to False.

False
frozen bool

Whether to freeze encoder. Defaults to False.

False
save_peft_only bool

Whether to save only the PEFT weights. Defaults to True.

True
lora_r int

LoRA r parameter. Defaults to 16.

16
lora_alpha int

LoRA alpha parameter. Defaults to 32.

32
lora_dropout float

LoRA dropout. Defaults to 0.1.

0.1
lora_target_modules Optional[List[str]]

LoRA target modules. Defaults to ["query", "value"].

['query', 'value']

modelgenerator.backbones.GenBioFM

Bases: HFSequenceBackbone

GenBioFM model

Note

Models using this interface include aido_protein_16b, aido_protein_16b_v1, aido_protein2structoken_16b, aido_protein_debug.

FSDP auto_wrap_policy is [modelgenerator.huggingface_models.fm4bio.modeling_fm4bio.FM4BioLayer]

Parameters:

Name Type Description Default
config_overwrites dict

Optional model arguments for PretrainedConfig. Defaults to None.

required
model_init_args dict

Optional model arguments passed to its init method. Defaults to None.

required
from_scratch bool

Whether to create the model from scratch. Defaults to False.

False
max_length int

Maximum sequence length. Defaults to 512.

None
use_peft bool

Whether to use LoRA PEFT. Defaults to False.

False
frozen bool

Whether to freeze encoder. Defaults to False.

False
save_peft_only bool

Whether to save only the PEFT weights. Defaults to True.

True
lora_r int

LoRA r parameter. Defaults to 16.

16
lora_alpha int

LoRA alpha parameter. Defaults to 16.

16
lora_dropout float

LoRA dropout. Defaults to 0.1.

0.1
lora_target_modules Optional[List[str]]

LoRA target modules. Defaults to ["query", "value", "key", "dense", "router"].

['query', 'value', 'key', 'dense', 'router']
lora_modules_to_save Optional[List[str]]

LoRA modules to save. Defaults to None.

None
lora_use_rslora bool

Whether to use RSLora. Defaults to False.

False

modelgenerator.backbones.Onehot

Bases: HFSequenceBackbone

Tokenizer-only model for one-hot encoding. Useful for baseline model testing (CNNs, linear, etc.)

Note

Models using this interface include dna_onehot and protein_onehot.

Does not contain any parameters, and cannot be used without an adapter.

Parameters:

Name Type Description Default
vocab_file str

Path to the vocabulary file. Defaults to "DNA-Transformers/src/transformers/models/rnabert/vocab.txt".

None
max_length Optional[int]

Maximum sequence length. Defaults to 512.

512

modelgenerator.backbones.GenBioCellFoundation

Bases: HFSequenceBackbone

GenBioCellFoundation model

Note

Models using this interface include aido_cell_100m, aido_cell_10m, and aido_cell_3m.

FSDP auto_wrap_policy is [modelgenerator.huggingface_models.cellfoundation.modeling_cellfoundation.CellFoundationLayer]

Parameters:

Name Type Description Default
config_overwrites dict

Optional model arguments for PretrainedConfig. Defaults to None.

required
model_init_args dict

Optional model arguments passed to its init method. Defaults to None.

required
from_scratch bool

Whether to create the model from scratch. Defaults to False.

False
max_length int

Maximum sequence length. Defaults to 512.

None
use_peft bool

Whether to use LoRA PEFT. Defaults to False.

False
frozen bool

Whether to freeze encoder. Defaults to False.

False
save_peft_only bool

Whether to save only the PEFT weights. Defaults to True.

True
lora_r int

LoRA r parameter. Defaults to 16.

16
lora_alpha int

LoRA alpha parameter. Defaults to 16.

16
lora_dropout float

LoRA dropout. Defaults to 0.1.

0.1
lora_target_modules Optional[List[str]]

LoRA target modules. Defaults to ["query", "value", "key", "dense", "router"].

['query', 'value', 'key', 'dense', 'router']
lora_modules_to_save Optional[List[str]]

LoRA modules to save. Defaults to None.

None
lora_use_rslora bool

Whether to use RSLora. Defaults to False.

False