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samadpls
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README.md
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language:
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- en
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pipeline_tag: text2text-generation
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---
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language:
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- en
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pipeline_tag: text2text-generation
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---
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# 🛢💬 Querypls-Prompt2SQL
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## Overview
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Querypls-Prompt2SQL is a 💬 text-to-SQL generation model developed by [samadpls](https://github.com/samadpls). It is designed for generating SQL queries based on user prompts.
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## Model Details
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- **License:** Apache-2.0
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- **Datasets:**
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- [samadpls/querypls-prompt2sql-dataset](https://huggingface.co/datasets/samadpls/querypls-prompt2sql-dataset)
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- [b-mc2/sql-create-context](https://huggingface.co/datasets/b-mc2/sql-create-context)
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- **Tags:**
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- stabilityai/StableBeluga-7B
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- langchain
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- opensource
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- stabilityai
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- SatbleBeluga-7B
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- **Language(s):** English
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- **Pipeline Tag:** Text2Text Generation
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## Model Usage
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To get started with the model in Python, you can use the following code:
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```python
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from transformers import pipeline, AutoTokenizer
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question = "how to get all employees from table0"
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prompt = f'Your task is to create SQL query of the following {question}, just SQL query and no text'
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tokenizer = AutoTokenizer.from_pretrained("samadpls/querypls-prompt2sql")
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pipe = pipeline(task='text-generation', model="samadpls/querypls-prompt2sql", tokenizer=tokenizer, max_length=200)
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result = pipe(prompt)
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print(result[0]['generated_text'])
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```
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Adjust the `question` variable with the desired question, and the generated SQL query will be printed.
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## Training Details
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The model was trained on Google Colab, and its purpose is to be used in the [Querypls](https://github.com/samadpls/Querypls) project with the following training and validation loss progression:
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```yaml
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Copy code
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Step Training Loss Validation Loss
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943 2.332100 2.652054
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1886 2.895300 2.551685
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2829 2.427800 2.498556
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3772 2.019600 2.472013
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4715 3.391200 2.465390
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```
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`However, note that the model may be too large to load in certain environments.`
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For more information and details, please refer to the provided [documentation](https://huggingface.co/stabilityai/StableBeluga-7B).
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## Model Card Authors
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- 🤖 [samadpls](https://github.com/samadpls)
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