AkashKhamkar/InSumT510k

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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