Instructions to use praeclarum/cuneiform with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use praeclarum/cuneiform with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("praeclarum/cuneiform") model = AutoModelForSeq2SeqLM.from_pretrained("praeclarum/cuneiform") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bdca0aa94b3c049fd7f40333808eab0dffd9ef64349730f4e1dfe72159cb43ae
- Size of remote file:
- 3.38 kB
- SHA256:
- d7ddf5921e87e22458a57b85c03ae5278d02bfcad2c1303fa11ab341d17f01b0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.