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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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- 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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</a> |
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This is an 8-bit quantized version of the `pszemraj/long-t5-tglobal-xl-16384-book-summary` model, The model has been compressed using `bitsandbytes` and can be loaded with low memory usage. |
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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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To use the model, install or upgrade `transformers`, `accelerate`, and `bitsandbytes`. Make sure to have `transformers>=4.28.0` and `bitsandbytes>0.37.2`. |
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```bash |
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pip install -U -q transformers bitsandbytes accelerate |
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``` |
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Load the model with `AutoTokenizer` and `AutoModelForSeq2SeqLM`: |
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```python |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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model_name = "pszemraj/long-t5-tglobal-xl-16384-book-summary-8bit" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForSeq2SeqLM.from_pretrained(model_name) |
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``` |
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## More information about long-t5-tglobal-xl-16384-book-summary |
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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. |
