Grimmerie 0.1.1

Functions for Prototyping, QOL and Sanity checking

specterize

A tiny helper package for generating SPECTER2 embeddings.

On first use, specterize() downloads the base model + adapter from Hugging Face and caches them locally.

Install

pip install grimmerie

Usage

from specterize import specterize

papers = [
    {'abstract': 'We introduce a new language representation model called BERT'},
    {
        'abstract': 'The dominant sequence transduction models are based on recurrent or convolutional neural networks'
    },
]

embeddings = specterize(papers, return_type='numpy')
print(embeddings.shape)  # (2, 768)

API

specterize(input_data, return_type='list', max_length=512)

• input_data: str, dict, list, or other iterable
• return_type: one of "list", "numpy", "tensor"
• max_length: tokenizer truncation max length (default 512)

Notes

• The first call is slower because model files are downloaded.
• Subsequent calls reuse the loaded model within the same Python process.