Instructions to use vvn/Text_to_SQL_BART_spider-three-ep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vvn/Text_to_SQL_BART_spider-three-ep with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vvn/Text_to_SQL_BART_spider-three-ep") model = AutoModelForSeq2SeqLM.from_pretrained("vvn/Text_to_SQL_BART_spider-three-ep", device_map="auto") - Notebooks
- Google Colab
- Kaggle
BART Large CNN model trained for converting NLP queries to SQL queries. The model was trained on the Spider dataset Link: https://yale-lily.github.io/spider
The model was trained using Google colab.
Hyperparameters: "num epochs" = 3 "learning rate" = 1e-5 "batch size" = 8 "weight decay" = 0.01 "max input length" = 256 "max target length" = 256 "model name" : "facebook/bart-large-cnn"
Link to the github repo containing training notebook: https://github.com/vanadnarayane26/Text_to_SQL_Spider-