Instructions to use Sumitp/Text_to_SQL_BART_sumit1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sumitp/Text_to_SQL_BART_sumit1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Sumitp/Text_to_SQL_BART_sumit1") model = AutoModelForSeq2SeqLM.from_pretrained("Sumitp/Text_to_SQL_BART_sumit1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sumitp/Text_to_SQL_BART_sumit1: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/Sumitp/Text_to_SQL_BART_sumit1/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Sumitp/Text_to_SQL_BART_sumit1@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sumitp/Text_to_SQL_BART_sumit1/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.63 GB
- Xet hash:
- cf2870babb1b584366ce98e9286243dbe90c07a0f4e9621d434423a1bdb29a3f
- Size of remote file:
- 1.63 GB
- SHA256:
- aba38f6662103f77aa08347c1b9fa77a1f00fa23bed901c83df16ad1b9938f00
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.