sentence-generalized-pooling 0.2.6

A library implementing generalized pooling for sentence transformers

Sentence Generalized Pooling

This library implements generalized pooling methods for sentence embeddings, based on the research paper "Enhancing Sentence Embedding with Generalized Pooling" by Qian Chen, Zhen-Hua Ling, and Xiaodan Zhu (COLING 2018).

Installation

pip install sentence-generalized-pooling

Usage

from sentence_transformers import SentenceTransformer
from sentence_generalized_pooling import GeneralizedSentenceTransformerMaker

# Load a base model
base_model = SentenceTransformer('all-MiniLM-L6-v2')

# Create a model with generalized pooling
maker = GeneralizedSentenceTransformerMaker(
    model_name=base_model,
    pooling_type=0,  # ADDITIVE pooling
    initalize=0,     # MEAN initialization
    device='cpu'
)

# Get the modified model
model = maker.get_model()

# Use the model
embeddings = model.encode(['Your sentence here'])

Features

• Supports both additive and dot-product pooling mechanisms
• Multiple initialization strategies: mean, noised, and random
• Multi-head attention mechanism
• Compatible with all sentence-transformer models

Citation

If you use this library in your research, please cite:

@inproceedings{chen-etal-2018-enhancing,
    title = "Enhancing Sentence Embedding with Generalized Pooling",
    author = "Chen, Qian  and
      Ling, Zhen-Hua  and
      Zhu, Xiaodan",
    booktitle = "Proceedings of the 27th International Conference on Computational Linguistics",
    year = "2018",
    url = "https://aclanthology.org/C18-1154",
    pages = "1815--1826",
}

License

This project is licensed under the MIT License - see the LICENSE file for details.