Instructions to use ViditRaj/BART-finetuned-Text2SQL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ViditRaj/BART-finetuned-Text2SQL with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ViditRaj/BART-finetuned-Text2SQL") model = AutoModelForSeq2SeqLM.from_pretrained("ViditRaj/BART-finetuned-Text2SQL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ViditRaj/BART-finetuned-Text2SQL: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/ViditRaj/BART-finetuned-Text2SQL/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://ViditRaj/BART-finetuned-Text2SQL@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ViditRaj/BART-finetuned-Text2SQL/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.63 GB
- Xet hash:
- 727c94162eb5b79173741339cf6a3817240036e9f0c7fd03c39fb775ccc42e89
- Size of remote file:
- 1.63 GB
- SHA256:
- 989e8b69c6f262b069f921073a13204e32715d64344698115140bc0422c5b776
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