Instructions to use X-Wang/pruned-mt5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use X-Wang/pruned-mt5-small with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("X-Wang/pruned-mt5-small") model = AutoModelForSeq2SeqLM.from_pretrained("X-Wang/pruned-mt5-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e99f879b71a6b2ebb02b731f8047bf8eefa66193f66c86d65e4bf466cf143dc5
- Size of remote file:
- 342 MB
- SHA256:
- c1f2bf983b1736e181dfaf878cb8b4466c786cc9e3d087f921f6dbde021fe6b3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.