---
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:
    ```bash
    pip install transformers
    ```
2. Load the model and tokenizer:
    ```python
    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.