Instructions to use Kithogue/T5_Question_Generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kithogue/T5_Question_Generation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Kithogue/T5_Question_Generation") model = AutoModelForSeq2SeqLM.from_pretrained("Kithogue/T5_Question_Generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Kithogue/T5_Question_Generation: direct link, hf CLI and curl.
- Browser
- Download file 164 Bytes
-
https://huggingface.co/Kithogue/T5_Question_Generation/resolve/main/README.md
- Command line
-
hf download hf://Kithogue/T5_Question_Generation/README.md
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curl -L -o README.md https://huggingface.co/Kithogue/T5_Question_Generation/resolve/main/README.md
164 Bytes
T5-base fine-tuned on SQuAD and CoQA datasets for question generation
language:
- en-us
tags:
- question-generation
license:
- MIT
datasets:
- SQuAD 2.0
- CoQA