Instructions to use alemiaschi/lit5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alemiaschi/lit5-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alemiaschi/lit5-large") model = AutoModelForSeq2SeqLM.from_pretrained("alemiaschi/lit5-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from alemiaschi/lit5-large: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/alemiaschi/lit5-large/resolve/main/training_args.bin
- Command line
-
hf download hf://alemiaschi/lit5-large/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/alemiaschi/lit5-large/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 8829751b5614f4cbcee2665c0745e18d995c90e7cad1d87172c05746b27b038f
- Size of remote file:
- 4.86 kB
- SHA256:
- 7baf045956a95b29fd9b7fbdfb8ebc852e3c2764cec4a1a4093da1355fe12807
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