Instructions to use contemmcm/df9829ef20751e04c89354d87ebedc3c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/df9829ef20751e04c89354d87ebedc3c with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("contemmcm/df9829ef20751e04c89354d87ebedc3c") model = AutoModelForSeq2SeqLM.from_pretrained("contemmcm/df9829ef20751e04c89354d87ebedc3c", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c68c2adff34bca8a2d21be44bfac39fa6341f1661d10926f206dd0780488992
- Size of remote file:
- 1.97 GB
- SHA256:
- c709ca80dc366d249a29308a5f2a5fb093f4741fa527bf54381cf0a9bf01e624
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.