| --- |
| language: en |
| tags: |
| - data-analytics |
| - dashboard |
| - AI |
| - visualization |
| license: mit |
| --- |
| |
| # AutoDashAnalyticsV1 LoRA Adapters |
|
|
| 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 |
|
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| - **Model Name:** AutoDashAnalyticsV1 |
| - **Version:** 1.0 |
| - **Language:** English |
| - **License:** MIT |
| - **Tags:** data-analytics, dashboard, AI, visualization |
|
|
| ## Model Description |
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| 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. |
|
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| ## Features |
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| - **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 |
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| 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. |
|
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| ## Performance |
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| 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 |
|
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| - The model is currently optimized for Relational databases. |
| - Future versions will include support for other database types. |
|
|
| ## License |
|
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| This project is licensed under the MIT License. |
|
|
| ## Acknowledgements |
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| 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}} |
| } |
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|