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:
# pip install -U transformers accelerate # 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
Download tokenizer.json from kiyam/lost-in-decoding-pag: direct link, hf CLI and curl.
- Browser
- Download file 2.42 MB
-
https://huggingface.co/kiyam/lost-in-decoding-pag/resolve/main/tokenizer.json
- Command line
-
hf download hf://kiyam/lost-in-decoding-pag/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/kiyam/lost-in-decoding-pag/resolve/main/tokenizer.json
2.42 MB
File too large to display, you can check the raw version instead.