Instructions to use adenhaus/mt5-large-tata with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adenhaus/mt5-large-tata with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("adenhaus/mt5-large-tata") model = AutoModelForSeq2SeqLM.from_pretrained("adenhaus/mt5-large-tata", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9da7ec466622b7325b0c230c3a68489a47dac60b08bcd2fc84074e704789df65
- Size of remote file:
- 16.3 MB
- SHA256:
- d842e6af904403ce6bf8ee58faffd9abad1682513c28c27454d81dc67eaf296c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.