Instructions to use ViditRaj/t5-finetuned-text2SQL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ViditRaj/t5-finetuned-text2SQL with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ViditRaj/t5-finetuned-text2SQL") model = AutoModelForSeq2SeqLM.from_pretrained("ViditRaj/t5-finetuned-text2SQL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ViditRaj/t5-finetuned-text2SQL: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/ViditRaj/t5-finetuned-text2SQL/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ViditRaj/t5-finetuned-text2SQL/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ViditRaj/t5-finetuned-text2SQL/resolve/main/pytorch_model.bin
892 MB
- Xet hash:
- 8635d24bd365c5da0d7e63a4e1e5ee0cf8392b5b9129a6a8167fc8e9da1fd61b
- Size of remote file:
- 892 MB
- SHA256:
- 0b2e06b6efebbf978d83ef193f7a030baf3e999bf713e7187e99518e753e4d73
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