Instructions to use choosistant/seq2seqmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use choosistant/seq2seqmodel with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("choosistant/seq2seqmodel") model = AutoModelForSeq2SeqLM.from_pretrained("choosistant/seq2seqmodel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cad33e86386b68021b684fe7923fa624ee03b198c481405b1bc5d18a9526d5ca
- Size of remote file:
- 1.63 GB
- SHA256:
- 2cb57b56f0ac2b42dbb69ec36e409d1a7155bb4ddec26c1cfcbe1a3cbb6ca956
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.