Instructions to use FiveC/ViTay-RI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FiveC/ViTay-RI with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FiveC/ViTay-RI") model = AutoModelForSeq2SeqLM.from_pretrained("FiveC/ViTay-RI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 879c5407ebd4c9046d913cddcfa641992562f730f1d8f5e2b8d07bc3b7e5e187
- Size of remote file:
- 1.58 GB
- SHA256:
- 352dd2c9407df9e0abc9689edaf9813ebf7b3d627d85b703f4ba7483ab35b6fc
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