# import model
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("sentence-transformers/clip-ViT-L-14")

# pick specific layers to train (note: you can add more layers to this list)
trainable_layers_list = ['projection']

# Apply freezing configuration
for name, param in model.named_parameters():

    # freeze all params
    param.requires_grad = False

    # unfreeze layers in trainable_layers_list
    if any(layer in name for layer in trainable_layers_list):
        param.requires_grad = True