Suiren-Dimer (1.8B)

Suiren-Dimer is a specialized version of the Suiren model, optimized through Continue Pre-training (CPT) from Suiren-Base. It specifically targets the modeling of intermolecular interactions.

Usage

You can load the model using the provided API in the GitHub repository.

import torch
from suiren_models import ModelLoader

# Initialize loader
loader = ModelLoader(config_path='config_name.yml')
# example: loader = ModelLoader(config_path='suiren-base.yml')

# Load model architecture
model = loader.load_model()

# Load pre-trained weights
loader.load_weights(model, 'path/to/checkpoint')

# Load normalizer from config
loader.load_normalizer()

# Load normalizer from checkpoint (optional)
#  loader.load_normalizer('path/to/normalizer')

# Move model to device
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = model.to(device)
model.eval()