About : This model can be used for text summarization.
The dataset on which it was fine tuned consisted of 10,323 articles.
The Data Fields :
- "Headline" : title of the article
- "articleBody" : the main article content
- "source" : the link to the readmore page.
The data splits were :
- Train : 8258.
- Vaildation : 2065.
How to use along with pipeline
from transformers import pipeline
from transformers import AutoTokenizer, AutoModelForSeq2Seq
tokenizer = AutoTokenizer.from_pretrained("AkashKhamkar/InSumT510k")
model = AutoModelForSeq2SeqLM.from_pretrained("AkashKhamkar/InSumT510k")
summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)
summarizer("Text for summarization...", min_length=5, max_length=50)
language:
- English
library_name: Pytorch
tags:
- Summarization
- T5-base
- Conditional Modelling
