Transformers
PyTorch
t5
text2text-generation
question-answering, multi-step-reasoning, multi-hop-reasoning
text-generation-inference
Instructions to use StonyBrookNLP/teabreac-preasm-large-drop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StonyBrookNLP/teabreac-preasm-large-drop with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("StonyBrookNLP/teabreac-preasm-large-drop") model = AutoModelForSeq2SeqLM.from_pretrained("StonyBrookNLP/teabreac-preasm-large-drop", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e30595d3dada11a3589e30dc604a325fd01b53b585e760dff5bb7dced66c93a9
- Size of remote file:
- 3.08 GB
- SHA256:
- fdfcbebe18d4d0708bdcd8c160bbcc7c0aa79b17aa7a9046544f510f4838bf88
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