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  ---
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  license:
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- - apache-2.0
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- - bsd-3-clause
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  tags:
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- - summarization
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- - summary
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- - booksum
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- - long-document
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- - long-form
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- - tglobal-xl
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- - XL
 
 
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  datasets:
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- - kmfoda/booksum
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  metrics:
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- - rouge
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  inference: false
 
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  ---
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- # long-t5-tglobal-xl-16384-book-summary: the 8-bit quantized version
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  <a href="https://colab.research.google.com/gist/pszemraj/c19e32baf876deb866c31cd46c86e893/long-t5-xl-accelerate-test.ipynb">
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  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
@@ -28,9 +31,9 @@ This is an 8-bit quantized version of the `pszemraj/long-t5-tglobal-xl-16384-boo
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  Refer to the [original model](https://huggingface.co/pszemraj/long-t5-tglobal-xl-16384-book-summary) for all details about the model architecture and training process. For more information on loading 8-bit models, refer to the `4.28.0` [release information](https://github.com/huggingface/transformers/releases/tag/v4.28.0) and the [example repository](https://huggingface.co/ybelkada/bloom-1b7-8bit).
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- - The total size of the model is only ~3.5 GB, much smaller than the original size.
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- - This allows for low-RAM loading, making it easier to use in memory-limited environments.
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- - `bitsandbytes` - AFAIK at time of writing - only works on GPU
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  ## Basic Usage
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  - This is an 8-bit quantized version of `pszemraj/long-t5-tglobal-xl-16384-book-summary`.
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  - It generalizes reasonably well to academic and narrative text.
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- - The XL checkpoint typically generates summaries that are considerably better from a human evaluation perspective.
 
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  ---
2
  license:
3
+ - apache-2.0
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+ - bsd-3-clause
5
  tags:
6
+ - summarization
7
+ - summary
8
+ - booksum
9
+ - long-document
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+ - long-form
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+ - tglobal-xl
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+ - XL
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+ - 8bit
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+ - quantized
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  datasets:
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+ - kmfoda/booksum
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  metrics:
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+ - rouge
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  inference: false
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+ pipeline_tag: summarization
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  ---
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+ # long-t5-tglobal-xl-16384-book-summary: 8-bit quantized version
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  <a href="https://colab.research.google.com/gist/pszemraj/c19e32baf876deb866c31cd46c86e893/long-t5-xl-accelerate-test.ipynb">
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  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
 
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  Refer to the [original model](https://huggingface.co/pszemraj/long-t5-tglobal-xl-16384-book-summary) for all details about the model architecture and training process. For more information on loading 8-bit models, refer to the `4.28.0` [release information](https://github.com/huggingface/transformers/releases/tag/v4.28.0) and the [example repository](https://huggingface.co/ybelkada/bloom-1b7-8bit).
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+ - The total size of the model is only ~3.5 GB (vs original 12 GB)
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+ - Enables low-RAM loading, making it easier to use in memory-limited environments like Colab
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+ - Requires `bitsandbytes` - AFAIK at time of writing, only works on GPU
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  ## Basic Usage
 
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  - This is an 8-bit quantized version of `pszemraj/long-t5-tglobal-xl-16384-book-summary`.
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  - It generalizes reasonably well to academic and narrative text.
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+ - The XL checkpoint typically generates summaries that are considerably better from a human evaluation perspective.