# Quantize and Optimize summarization model (Seq2SeqLM)

**URL:** <https://discuss.huggingface.co/t/quantize-and-optimize-summarization-model-seq2seqlm/21549>\
**Category:** Beginners\
**Created:** [August 12, 2022, 3:44am UTC](https://discuss.huggingface.co/t/quantize-and-optimize-summarization-model-seq2seqlm/21549 "2022-08-12T03:44:55Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Z3K3](https://avatars.discourse-cdn.com/v4/letter/z/a3d4f5/32.png) [@Z3K3](https://discuss.huggingface.co/u/Z3K3)\
**Post date:** [August 12, 2022, 3:44am UTC](https://discuss.huggingface.co/t/quantize-and-optimize-summarization-model-seq2seqlm/21549/1 "2022-08-12T03:44:55Z")

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I want to Quantize and Optimize the [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn), so i can get faster summarization results while reducing the size of the model, i have looked at [Optimum with Huggingface](https://huggingface.co/blog/optimum-inference), but they dont support summarization, and when you try to use it with seq2seq models it actually makes the model larger. I want to know if there any other ways i could optimize or quantize the [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn), for better speeds, while still getting similar accuracy