metadata
widget:
- text: >-
context: I would hope that Phylicia Rashad would apologize now that
@missjillscott has! You cannot discount 30 victims who come with similar
stories.— JDWhitner (@JDWhitner) July 7, 2015, question: what should
phylicia rashad do now?
example_title: example 1
- text: >-
context: I would hope that Phylicia Rashad would apologize now that
@missjillscott has! You cannot discount 30 victims who come with similar
stories.— JDWhitner (@JDWhitner) July 7, 2015, question: how many victims
have come forward?
example_title: example 2
- text: >-
context: The news about Vegas is devastating. Sending all our love to the
people there right now ❤️❤️❤️— HAIM (@HAIMtheband) October 2, 2017,
question: where is the news devastating?
example_title: example 3
cardiffnlp/flan-t5-base-tweet-qa
This is google/flan-t5-base fine-tuned on cardiffnlp/super_tweeteval (tweet_qa).
Usage
from transformers import pipeline
pipe = pipeline('text2text-generation', model="cardiffnlp/flan-t5-base-tweet-qa")
output = pipe("context: I would hope that Phylicia Rashad would apologize now that @missjillscott has! You cannot discount 30 victims who come with similar stories.— JDWhitner (@JDWhitner) July 7, 2015, question: what should phylicia rashad do now?")