Instructions to use Oscarshih/long-t5-base-SQA-15ep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Oscarshih/long-t5-base-SQA-15ep with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Oscarshih/long-t5-base-SQA-15ep") model = AutoModelForSeq2SeqLM.from_pretrained("Oscarshih/long-t5-base-SQA-15ep", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da81841ef84db698b11a1f460e9db2c5eab0721107adfae23046e3dcdc30ab33
- Size of remote file:
- 1.05 GB
- SHA256:
- d2fe8ce66b749d3e1ad44b5667f9efdf2f2477fd030615ce97128e25e9686d0a
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