Model Details
Full Model IDpszemraj/long-t5-tglobal-base-sci-simplify
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)208.1K
Likes10
Last Modified12/29/2025
Author / Orgpszemraj
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("summarization", model="pszemraj/long-t5-tglobal-base-sci-simplify")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchonnxsafetensorslongt5text2text-generationlay summariespaper summariesbiologymedicalsummarizationendataset:pszemraj/scientific_lay_summarisation-plos-normbase_model:google/long-t5-tglobal-basebase_model:quantized:google/long-t5-tglobal-baselicense:apache-2.0endpoints_compatibleregion:us
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models📝 Task: Summarization
This model is designed for the Summarization task. Explore more models for this use case.
All Summarization Models →📊 Popularity
⬇ Downloads208.1K
❤️ Community Likes10
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.