Transformers
PyTorch
JAX
English
t5
text2text-generation
qa
question
answering
SQuAD
data2text
metric
nlg
t5-small
text-generation-inference
Instructions to use ThomasNLG/t5-qa_webnlg_synth-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThomasNLG/t5-qa_webnlg_synth-en with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ThomasNLG/t5-qa_webnlg_synth-en") model = AutoModelForSeq2SeqLM.from_pretrained("ThomasNLG/t5-qa_webnlg_synth-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1522f34a92aec2190205f37b4591eee1a70aefd34288c40afee813cdbe7a4662
- Size of remote file:
- 242 MB
- SHA256:
- 15a79182609f6db9c0005d08a464c14b69e4831cbdecaaf8afa96826bc256073
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