Transformers
PyTorch
t5
generative-retrieval
information-retrieval
msmarco
robustness
reproducibility
text-generation-inference
Instructions to use kiyam/lost-in-decoding-pag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kiyam/lost-in-decoding-pag with Transformers:
# Load model directly from transformers import AutoTokenizer, T5ForLexicalSemanticGeneration tokenizer = AutoTokenizer.from_pretrained("kiyam/lost-in-decoding-pag") model = T5ForLexicalSemanticGeneration.from_pretrained("kiyam/lost-in-decoding-pag", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35145921d285e8043caf3f0b9c414a20d38811375855a86111e2349dc8cde5fb
- Size of remote file:
- 431 Bytes
- SHA256:
- c71b3f8892a3ca56cac5615e641aa34a8f2500bbebbdbc7406d99166dad49555
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