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
File size: 501 Bytes
a0f3491 b4388d7 6976fea b4388d7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | 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- |