Instructions to use parkervg/destt5-schema-prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use parkervg/destt5-schema-prediction with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("parkervg/destt5-schema-prediction") model = AutoModelForSeq2SeqLM.from_pretrained("parkervg/destt5-schema-prediction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a364f8d1d8e50cf9525276b447908e19649a7b8ebab30882edb4093f538a088b
- Size of remote file:
- 3.18 kB
- SHA256:
- ac862633dd50217b417b1702b6bab2210b5fec4ad55a176066d30afeddbbd2b0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.