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MODEL Listed

pegasus xsum

Pegasus XSum is a specialized transformer model engineered specifically for extreme summarization. Unlike general-purpose LLMs that often produce extractive summaries, Pegasus is designed for abstractive tasks, meaning it synthesizes a concise, single-sentence summary that captures the essence of a document without simply copying phrases. For developers, this makes it an ideal choice for generating headlines, notification snippets, or metadata for large content libraries. It is highly efficient for production pipelines where low-latency, high-density information extraction is required. Integration is straightforward via Hugging Face, and its Apache-2.0 license ensures flexibility for commercial deployment. While it lacks the broad reasoning of a GPT-4, it outperforms general models in specific 'one-sentence' distillation tasks by avoiding the verbosity typically associated with larger models.

googlesummarization
01 / MODEL CARD

Model card

Pegasus XSum is a specialized transformer model engineered specifically for extreme summarization. Unlike general-purpose LLMs that often produce extractive summaries, Pegasus is designed for abstractive tasks, meaning it synthesizes a concise, single-sentence summary that captures the essence of a document without simply copying phrases. For developers, this makes it an ideal choice for generating headlines, notification snippets, or metadata for large content libraries. It is highly efficient for production pipelines where low-latency, high-density information extraction is required. Integration is straightforward via Hugging Face, and its Apache-2.0 license ensures flexibility for commercial deployment. While it lacks the broad reasoning of a GPT-4, it outperforms general models in specific 'one-sentence' distillation tasks by avoiding the verbosity typically associated with larger models.

Model typesummarization
Providergoogle
LicenseApache-2.0
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/google/pegasus-xsum
View model source
Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: google/pegasus-xsum
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model google/pegasus-xsum
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model google/pegasus-xsum README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('google/pegasus-xsum')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/google/pegasus-xsum.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/google/pegasus-xsum.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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