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schema-aware-denoising-bart-large-cnn-text2sql
shahrukhx01/schema-aware-denoising-bart-large-cnn-text2sql
schema-aware-denoising-bart-large-cnn-text2sql is a machine learning model from shahrukhx01. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
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At a glance
- Library
- transformers
- Model type
- bart
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Aug 21, 2021
- SHA
- 71c954ec
Try a prompt
Model card
From the Hugging Face model README
from transformers import BartTokenizer, BartForConditionalGeneration, BartConfig
model = BartForConditionalGeneration.from_pretrained('shahrukhx01/schema-aware-denoising-bart-large-cnn-text2sql')
tokenizer = BartTokenizer.from_pretrained('shahrukhx01/schema-aware-denoising-bart-large-cnn-text2sql')
## add NL query with table schema
question = "What is terrence ross' nationality? </s> <col0> Player : text <col1> No. : text <col2> Nationality : text <col3> Position : text <col4> Years in Toronto : text <col5> School/Club Team : text"
inputs = tokenizer([question], max_length=1024, return_tensors='pt')
# Generate SQL
text_query_ids = model.generate(inputs['input_ids'], num_beams=4, min_length=0, max_length=125, early_stopping=True)
prediction = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in text_query_ids][0]
print(prediction)
- Library
- transformers
- Type
- bart
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Aug 21, 2021