Instructions to use FiveC/ViTay with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FiveC/ViTay with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FiveC/ViTay") model = AutoModelForSeq2SeqLM.from_pretrained("FiveC/ViTay", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 641bc1cd619d9afe859529c819c6edd35518b337287232acb603d18e98a37cf7
- Size of remote file:
- 1.58 GB
- SHA256:
- 4e15c684c17c788d5f9636e5dc3bd18ba94281ab5038a0c1b592d05f2873e7f0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.