JetRunner/BERT-of-Theseus

⛵️The official PyTorch implementation for "BERT-of-Theseus: Compressing BERT by Progressive Module Replacing" (EMNLP 2020).

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Emerging

This project helps machine learning engineers and researchers reduce the computational cost of large BERT models without significantly losing performance. It takes an existing, fine-tuned BERT model and outputs a smaller, faster version. This is ideal for those deploying natural language processing models in resource-constrained environments.

315 stars. No commits in the last 6 months.

Use this if you need to compress a BERT model to make it run faster or use less memory, especially for deployment on edge devices or in high-throughput systems.

Not ideal if you are looking for a pre-trained model for non-natural language processing tasks or if your primary concern is improving model accuracy rather than efficiency.

natural-language-processing model-compression deep-learning-deployment computational-efficiency
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 17 / 25

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Stars

315

Forks

39

Language

Python

License

Apache-2.0

Last pushed

Jun 12, 2023

Commits (30d)

0

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