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InSumT510k
AkashKhamkar/InSumT510k
InSumT510k is a machine learning model from AkashKhamkar. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as afl-3.0.
--- About : This model can be used for text summarization.
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At a glance
- Library
- transformers
- License
- afl-3.0
- Model type
- t5
- Access
- Public
- Created
- Aug 10, 2022
- Updated
- Aug 12, 2022
- SHA
- 4def6377
Model card
From the Hugging Face model README
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
- Library
- transformers
- Type
- t5
- License
- afl-3.0
- Created
- Aug 10, 2022
- Updated
- Aug 12, 2022