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README.md

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+---
+language: en
+tags:
+- data-analytics
+- dashboard
+- AI
+- visualization
+license: mit
+---
+
+# AutoDashAnalyticsV1GGUF
+
+AutoDashAnalyticsV1GGUF is a powerful tool designed to automate the creation of dashboards from various databases using advanced AI techniques. This model connects to SQL databases and provides interactive data visualizations through user prompts.
+
+## Model Details
+
+- **Model Name:** AutoDashAnalyticsV1GGUF
+- **Version:** 1.0
+- **Language:** English
+- **License:** MIT
+- **Tags:** data-analytics, dashboard, AI, visualization
+
+## Model Description
+
+AutoDashAnalyticsV1GGUF is developed to simplify and enhance the data analysis process for companies. It leverages a fine-tuned large language model trained on extensive datasets specifically for data analysis. The tool enables users to create detailed and interactive dashboards with minimal effort.
+
+## Features
+
+- **Automated Dashboard Creation:** Automatically generates dashboards from SQL databases.
+- **Interactive Visualizations:** Allows users to interact with the data through prompts.
+- **Advanced AI Capabilities:** Utilizes a fine-tuned LLM for comprehensive data analysis.
+- **Customization:** Provides options for customizing the visualizations and data representation.
+
+
+## Training Data
+
+The model is trained on a diverse dataset comprising various SQL databases and data visualization examples. This ensures robust performance across different data types and structures.
+
+## Performance
+
+AutoDashAnalyticsV1GGUF has been tested extensively to ensure high accuracy and reliability in generating dashboards. The model can handle large datasets and provide insightful visualizations efficiently.
+
+## Limitations
+
+- The model is currently optimized for Relational databases.
+- Future versions will include support for other database types.
+
+## License
+
+This project is licensed under the MIT License.
+
+## Acknowledgements
+
+We acknowledge the contributions of the open-source community and the developers who have supported this project.
+
+## Citation
+
+If you use this model in your research, please cite it as follows:
+@misc{AutoDashAnalyticsV1GGUF,
+title = {AutoDashAnalyticsV1GGUF},
+year = {2024},
+publisher = {Hugging Face},
+journal = {Hugging Face repository},
+howpublished = {\url{https://huggingface.co/techcodebhavesh/AutoDashAnalyticsV1GGUF}}
+}