valhalla/t5-base-qg-hl

Model

T5 for question-generation

12

21 commits

1 linked in READMEs

updated Jun 23, 2021

See the code

README

T5 for question-generation

This is t5-base model trained for answer aware question generation task. The answer spans are highlighted within the text with special highlight tokens.

You can play with the model using the inference API, just highlight the answer spans with <hl> tokens and end the text with </s>. For example

<hl> 42 <hl> is the answer to life, the universe and everything. </s>

For more deatils see this repo.

Model in action 🚀

You'll need to clone the repo.

Open In Colab

from pipelines import pipeline
nlp = pipeline("question-generation", model="valhalla/t5-base-qg-hl")
nlp("42 is the answer to life, universe and everything.")
=> [{'answer': '42', 'question': 'What is the answer to life, universe and everything?'}]
endpoints_compatible
pytorch
question-generation
t5
text2text-generation
text-generation-inference
transformers

valhalla/t5-base-qg-hl

Model

T5 for question-generation

12

21 commits

1 linked in READMEs

updated Jun 23, 2021

See the code

README

T5 for question-generation

This is t5-base model trained for answer aware question generation task. The answer spans are highlighted within the text with special highlight tokens.

You can play with the model using the inference API, just highlight the answer spans with <hl> tokens and end the text with </s>. For example

<hl> 42 <hl> is the answer to life, the universe and everything. </s>

For more deatils see this repo.

Model in action 🚀

You'll need to clone the repo.

Open In Colab

from pipelines import pipeline
nlp = pipeline("question-generation", model="valhalla/t5-base-qg-hl")
nlp("42 is the answer to life, universe and everything.")
=> [{'answer': '42', 'question': 'What is the answer to life, universe and everything?'}]
endpoints_compatible
pytorch
question-generation
t5
text2text-generation
text-generation-inference
transformers