Summarization
Transformers
Safetensors
pegasus
text2text-generation
title-generation
scientific-text
scihigh-2026
fire-2026
Instructions to use kckrish21/SciHigh2026-Task2-PEGASUS-XSum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kckrish21/SciHigh2026-Task2-PEGASUS-XSum with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="kckrish21/SciHigh2026-Task2-PEGASUS-XSum")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kckrish21/SciHigh2026-Task2-PEGASUS-XSum") model = AutoModelForSeq2SeqLM.from_pretrained("kckrish21/SciHigh2026-Task2-PEGASUS-XSum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from kckrish21/SciHigh2026-Task2-PEGASUS-XSum: direct link, hf CLI and curl.
- Browser
- Download file 6.6 MB
-
https://huggingface.co/kckrish21/SciHigh2026-Task2-PEGASUS-XSum/resolve/main/tokenizer.json
- Command line
-
hf download hf://kckrish21/SciHigh2026-Task2-PEGASUS-XSum/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/kckrish21/SciHigh2026-Task2-PEGASUS-XSum/resolve/main/tokenizer.json
6.6 MB
File too large to display, you can check the raw version instead.