sqlcoder-70b-alpha
Maintainer: defog
190
👁️
| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The sqlcoder-70b-alpha is a capable large language model for natural language to SQL generation, developed by Defog, Inc. It outperforms all generalist models, including GPT-4, on text to SQL tasks. The model was fine-tuned from the CodeLlama-70B model.
Similar models include the defog-sqlcoder-7b-2 and the starcoder and starcoder2-15b models, which are also large language models with capabilities for code generation.
Model inputs and outputs
The sqlcoder-70b-alpha model takes natural language text as input and generates SQL queries as output. This makes it useful for tasks like data exploration and analytics, where users can describe their information needs in plain language and have the model translate that to the corresponding SQL.
Inputs
- Natural language text describing an information need or data request
Outputs
- SQL queries that can be executed against a database to retrieve the requested information
Capabilities
The sqlcoder-70b-alpha model is highly capable at translating natural language descriptions into accurate and executable SQL queries. It outperforms other generalist language models on this task, making it a valuable tool for users who need to interact with databases but may not be skilled in SQL.
What can I use it for?
The sqlcoder-70b-alpha model is intended to be used by non-technical users to explore and understand data stored in SQL databases. It can act as an analytics assistant, allowing users to describe their information needs in plain language and have the model generate the relevant SQL queries.
However, the model has not been trained to handle malicious requests, so it should only be used by users with read-only access to databases. It is not suitable for use as a database administration tool.
Things to try
One interesting thing to try with the sqlcoder-70b-alpha model is to provide it with a series of natural language prompts describing different information needs, and observe how it translates those prompts into SQL. This can help you understand the model's strengths and limitations in handling various types of data requests.
You can also experiment with providing the model with prompts that combine multiple pieces of information, such as filtering, grouping, and ordering, to see how it handles more complex SQL queries.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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