pszemraj/led-base-book-summary

summarization model by pszemraj

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The Longformer Encoder-Decoder (LED) for Narrative-Esque Long Text Summarization is a model I fine-tuned from allenai/led-base-16384 to condense extensive technical, academic, and narrative content in a fairly generalizable way. The model was trained on the BookSum dataset released by SalesForce, which leads to the bsd-3-clause license. The training process involved 16 epochs with parameters tweaked to facilitate very fine-tuning-type training (super low learning rate). Model checkpoint: pszemraj/led-base-16384-finetuned-booksum. This model is the smallest/fastest booksum-tuned model I have worked on. If you're looking for higher quality summaries, check out: There are also other variants on other datasets etc on my hf profile, feel free to try them out :) I recommend using encodernorepeatngramsize=3 when calling the pipeline object, as it enhances the summary quality by encouraging the use of new vocabulary…

pszemraj/led-base-book-summary on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. LED-Based Summarization Model: Condensing Long and Technical Information
  2. Key Features and Use Cases
  3. Training Details
  4. Other Related Checkpoints
  5. Basic Usage
  6. Simplified Usage with TextSum

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Model overview

pszemraj/led-base-book-summary is a summarization model repository published by pszemraj on Hugging Face. The source reports the transformers library.

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Model facts

Task
summarization
Library
transformers
Recent downloads (30 days)
709
Cumulative likes
67
Hugging Face trending score
0
Reported safetensors parameters
161,894,745
Architecture
LEDForConditionalGeneration
License
apache-2.0
Access
Not gated by Hugging Face
Created
2022-03-02T23:29:05.000Z
Last modified
2025-12-29T03:38:08.000Z

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