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:
- 932edff417d183b6258b27df20bcfcca7498e5bfb3f2461357c9b6e3ca22374c
- Size of remote file:
- 1.58 GB
- SHA256:
- 5d85b85c643673c0e4d92a0506dbae02bd7772627eb1049280932c7bd4fae9e1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.