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:
- db74fdb2b6b0b55523fe89b485333aaeeacf162f11b3a060960bab0950eec901
- Size of remote file:
- 5.97 kB
- SHA256:
- e31f7824d3e8327292dbb265e7c35761abc48e6291550d7f5a23751d8e03573c
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