<p>The authorities released their code:
<a href="https://github.com/IST-DASLab/sparsegpt" rel="nofollow noreferrer">https://github.com/IST-DASLab/sparsegpt</a></p>

CC BY-SA 4.0
2023-03-24T03:52:28.137Z
2023-03-24T03:52:28.137Z
user68072
<p>SparseGPT: <a href="https://arxiv.org/pdf/2301.00774.pdf" rel="nofollow noreferrer">https://arxiv.org/pdf/2301.00774.pdf</a></p>
<p>Pruning on the super large language model based on the Transformers structure has achieved a high compression rate with a small loss of accuracy. Is there any related code reproduction or research?</p>
<p>Someone mentioned on <a href="https://github.com/karpathy/nanoGPT" rel="nofollow noreferrer">https://github.com/karpathy/nanoGPT</a>, but no response.</p>

<natural-language-processing><large-language-models>
SparseGPT code reproduction
user68072
# SparseGPT code reproduction

(Asked by: username_0 on 2023-03-14)

SparseGPT: <https://arxiv.org/pdf/2301.00774.pdf>

Pruning on the super large language model based on the Transformers structure has achieved a high compression rate with a small loss of accuracy. Is there any related code reproduction or research?

Someone mentioned on <https://github.com/karpathy/nanoGPT>, but no response.

**Tags:** natural-language-processing, large-language-models


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## 1 answers

### Answer by username_0 on 2023-03-24. Score: 1 | Accepted answer

The authorities released their code:
<https://github.com/IST-DASLab/sparsegpt>


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