Instructions to use Saddammm/Model300T5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Saddammm/Model300T5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Saddammm/Model300T5") model = AutoModelForSeq2SeqLM.from_pretrained("Saddammm/Model300T5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Saddammm/Model300T5: direct link, hf CLI and curl.
- Browser
- Download file 4.47 kB
-
https://huggingface.co/Saddammm/Model300T5/resolve/main/training_args.bin
- Command line
-
hf download hf://Saddammm/Model300T5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Saddammm/Model300T5/resolve/main/training_args.bin
4.47 kB
- Xet hash:
- d2229c4b8917fdb59310631cf823fa7371400c968607b62e9cd53c76a401c072
- Size of remote file:
- 4.47 kB
- SHA256:
- 9eefad14ffe6ab4c089a6f12f31c528de0012f7a62d24c1c839369475727dd62
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