Instructions to use Aries/T5_question_answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aries/T5_question_answering with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Aries/T5_question_answering") model = AutoModelForSeq2SeqLM.from_pretrained("Aries/T5_question_answering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Aries/T5_question_answering: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/Aries/T5_question_answering/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Aries/T5_question_answering/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Aries/T5_question_answering/resolve/main/flax_model.msgpack
892 MB
- Xet hash:
- d09f6c43e1c601a5a81e379f6c0bfd5232c6e6dc0395a78da3d7f11ae9d24e0f
- Size of remote file:
- 892 MB
- SHA256:
- 27ca317249328fd0f721b1e9c8c8f8d9bd65c7e1adc31e0892ce05c6777aee9c
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