models¶
models
provide a collection of pre-trained models.
Model Class¶
In the transformers
library, the names of model classes can sometimes be misleading.
While these classes support both regression and classification tasks, their names often include xxxForSequenceClassification
, which may imply they are only for classification.
To avoid this ambiguity, MultiMolecule provides a set of model classes with clear, intuitive names that reflect their intended use:
multimolecule.AutoModelForSequencePrediction
: Sequence Predictionmultimolecule.AutoModelForTokenPrediction
: Token Predictionmultimolecule.AutoModelForContactPrediction
: Contact Prediction
Each of these models supports both regression and classification tasks, offering flexibility and precision for a wide range of applications.
Contact Prediction¶
Contact prediction assign a label to each pair of token in a sentence. One of the most common contact prediction tasks is protein distance map prediction. Protein distance map prediction attempts to find the distance between all possible amino acid residue pairs of a three-dimensional protein structure
Nucleotide Prediction¶
Similar to Token Classification, but removes the <bos>
token and the <eos>
token if they are defined in the model config.
<bos>
and <eos>
tokens
In tokenizers provided by MultiMolecule, <bos>
token is pointed to <cls>
token, and <sep>
token is pointed to <eos>
token.
Usage¶
Build with multimolecule.AutoModel
s¶
Direct Access¶
All models can be directly loaded with the from_pretrained
method.
Build with transformers.AutoModel
s¶
While we use a different naming convention for model classes, the models are still registered to corresponding transformers.AutoModel
s.
import multimolecule
before use
Note that you must import multimolecule
before building the model using transformers.AutoModel
.
The registration of models is done in the multimolecule
package, and the models are not available in the transformers
package.
The following error will be raised if you do not import multimolecule
before using transformers.AutoModel
:
Python | |
---|---|
Initialize a vanilla model¶
You can also initialize a vanilla model using the model class.