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neuralmagic
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oBERT-12-upstream-pruned-unstructured-90

Transformers
PyTorch
English
bert
oBERT
sparsity
pruning
compression
Inference Endpoints
Model card Files Community
ekurtic commited on
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@@ -31,9 +31,11 @@ Sparsity: 90%
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  Number of layers: 12
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  ```
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- Code: _coming soon_
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- ## BibTeX entry and citation info
 
 
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  ```bibtex
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  @article{kurtic2022optimal,
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  title={The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models},
 
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  Number of layers: 12
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  ```
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+ Code: [https://github.com/neuralmagic/sparseml/tree/main/research/optimal_BERT_surgeon_oBERT](https://github.com/neuralmagic/sparseml/tree/main/research/optimal_BERT_surgeon_oBERT)
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+ If you find the model useful, please consider citing our work.
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+
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+ ## Citation info
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  ```bibtex
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  @article{kurtic2022optimal,
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  title={The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models},