README.md

metadata

datasets:
  - Kasivs/SearchSQL
language:
  - en
metrics:
  - code_eval
library_name: flair
pipeline_tag: text2text-generation
tags:
  - code
license: llama2

SQLCreator

Model Overview

This model is designed to generate SQL queries based on input prompts. It is based on GPT-2 and trained with custom datasets.

Usage

To use this model, follow these steps:

1. Install the necessary libraries:

   pip install transformers
   

2. Load the model and tokenizer:

   from transformers import AutoModelForCausalLM, AutoTokenizer
   
   model_name = “Kasivs/SQLCreator"
   tokenizer = AutoTokenizer.from_pretrained(model_name)
   model = AutoModelForCausalLM.from_pretrained(model_name)
   
   # Example usage
   inputs = tokenizer("SELECT * FROM users WHERE", return_tensors="pt")
   outputs = model.generate(inputs["input_ids"])
   print(tokenizer.decode(outputs[0]))
   

Training

Details about how the model was trained, including dataset information and training parameters.

License

Specify the license under which the model is distributed.

Citation

Provide citation information if applicable.

Contact

Your contact information or any related resources.