Question Answering
Transformers
PyTorch
English
t5
text2text-generation
triviaqa
t5-base
lm-head
closed-book
pipeline:question-answering
text-generation-inference
Instructions to use deep-learning-analytics/triviaqa-t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deep-learning-analytics/triviaqa-t5-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="deep-learning-analytics/triviaqa-t5-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("deep-learning-analytics/triviaqa-t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("deep-learning-analytics/triviaqa-t5-base") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
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