allenai/smashed
SMASHED is a toolkit designed to apply transformations to samples in datasets, such as fields extraction, tokenization, prompting, batching, and more. Supports datasets from Huggingface, torchdata iterables, or simple lists of dictionaries.
This tool helps machine learning engineers preprocess text data for language models. It takes raw text (like sentences or documents) as input and transforms it into numerical tokens, correctly formatted with padding and attention masks. It's designed for ML engineers building or fine-tuning models that consume large text datasets.
Used by 2 other packages. No commits in the last 6 months. Available on PyPI.
Use this if you need to efficiently prepare diverse text datasets for training or inference with transformer-based language models, handling tokenization, length constraints, and batching.
Not ideal if you're looking for a general-purpose data cleaning or ETL tool for non-textual data or for users who are not working with machine learning models.
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Language
Python
License
Apache-2.0
Category
Last pushed
May 24, 2024
Commits (30d)
0
Dependencies
7
Reverse dependents
2
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