Transformers
PyTorch
TensorFlow
English
t5
text2text-generation
Generative Question Answering
text-generation-inference
Instructions to use MaRiOrOsSi/t5-base-finetuned-question-answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaRiOrOsSi/t5-base-finetuned-question-answering with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MaRiOrOsSi/t5-base-finetuned-question-answering") model = AutoModelForSeq2SeqLM.from_pretrained("MaRiOrOsSi/t5-base-finetuned-question-answering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Update Hugging Face dataset ID
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README.md
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language: en
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datasets:
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- duorc
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widget:
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- text: "question: Is Giacomo Italian? context: Giacomo is 25 years old and he was born in Tuscany"
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- text: "question: Where does Christian come from? context: Christian is a student of UNISI but he come from Caserta"
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- text: "question: Is the dog coat grey? context: You have a beautiful dog with a brown coat"
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tags:
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- Generative Question Answering
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---
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# T5 for Generative Question Answering
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language: en
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tags:
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- Generative Question Answering
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datasets:
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- ibm/duorc
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widget:
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- text: 'question: Is Giacomo Italian? context: Giacomo is 25 years old and he was
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born in Tuscany'
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- text: 'question: Where does Christian come from? context: Christian is a student
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of UNISI but he come from Caserta'
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- text: 'question: Is the dog coat grey? context: You have a beautiful dog with a
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brown coat'
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# T5 for Generative Question Answering
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