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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: mit
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+ base_model:
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+ - deepseek-ai/DeepSeek-V3.1
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+ tags:
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+ - dash
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+ - folium
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+ - deepseek-v3.1-4bit
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+ - DeepSeek
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+ - DeepSeek-V3.1-4bit
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+ - Dash
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+ - Folium
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+ ---
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+ # Model Card: World Explorer with DeepSeek AI
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+
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+ ## Model Details
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+
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+ **Model Name:** World Explorer with DeepSeek AI
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+ **Model Type:** Geographic Information System with AI Integration
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+ **Architecture:** Dash Web Application with Folium Maps and DeepSeek Language Model
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+ **Integration:** mlx-community/DeepSeek-V3.1-4bit, Dash, Folium
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+ **Version:** 1.0.0
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+ **Release Date:** September 5, 2025
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+ **Developers:** Martin Rivera
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+
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+ ## Model Description
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+
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+ The World Explorer with DeepSeek AI is an interactive web application that combines geographic visualization with advanced language model capabilities. It integrates:
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+
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+ - **mlx-community/DeepSeek-V3.1-4bit**: A quantized version of the DeepSeek V3.1 language model optimized for MLX
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+ - **Dash**: A Python framework for building analytical web applications
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+ - **Folium**: A Python library for creating interactive maps and geographic visualizations
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+
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+ This application provides an immersive experience for exploring world geography, country information, capitals, and famous landmarks through an intuitive interface powered by AI.
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+
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+ ## Intended Use
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+
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+ This model is designed for:
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+
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+ - Educational purposes for learning about world geography
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+ - Tourism planning and destination research
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+ - Geographic data visualization and exploration
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+ - Demonstrating the integration of language models with geographic information systems
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+ - Research in human-computer interaction with AI-powered geographic interfaces
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+
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+ ## Features
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+
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+ ### Core Capabilities
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+ - Interactive world map with precise geographic coordinates
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+ - Country information including capitals and coordinates
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+ - Detailed landmark data with exact geographic positions
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+ - AI-powered natural language queries about geographic information
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+ - Real-time responses to questions about countries, capitals, and landmarks
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+
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+ ### Technical Integration
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+ - MLX-optimized DeepSeek model for efficient inference
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+ - Responsive Dash web interface with Bootstrap styling
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+ - Folium-based interactive maps with marker clusters
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+ - Multi-threaded model loading for non-blocking user experience
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+ - Advanced query parsing for geographic context understanding
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+
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+ ## Data
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+
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+ The application uses a comprehensive dataset of 10 countries with:
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+
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+ - Precise coordinates for each country's capital
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+ - 30 famous landmarks with exact geographic coordinates
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+ - Curated information about each geographic feature
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+
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+ ### Countries Included:
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+ - France, United States, Japan, India, Brazil
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+ - Egypt, Australia, Italy, China, United Kingdom
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+
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+ ### Landmark Examples:
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+ - Eiffel Tower (48.858222, 2.2945)
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+ - Great Wall of China (40.68, 117.23)
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+ - Taj Mahal (27.175, 78.041944)
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+ - Statue of Liberty (40.689167, -74.044444)
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+ - Pyramids of Giza (29.9725, 31.128333)
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+
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+ ## Installation and Usage
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+
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+ ### Requirements
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+ ```bash
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+ dash==2.14.2
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+ dash-bootstrap-components==1.5.0
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+ folium==0.15.1
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+ pandas==2.1.4
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+ numpy==1.26.4
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+ mlx==0.0.6
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+ transformers==4.37.2
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+ ```
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+
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+ ### Installation
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+ ```bash
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+ git clone <repository>
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+ cd world-explorer-deepseek
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+ pip install -r requirements.txt
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+ ```
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+
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+ ### Running the Application
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+ ```bash
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+ python app.py
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+ ```
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+ The application will be available at `http://localhost:8050`
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+
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+ ### Model Setup
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+ The application requires the MLX-optimized DeepSeek model from:
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+ ```
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+ MODEL_PATH = "/Users/martinrivera/deepseek_v3_1_4bit_mlx/deepseek_v3_4bit" (Modify with your own MODEL_PATH = "path/to DeepSeek")
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+ ```
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+
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+ ## Performance
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+
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+ ### Response Quality
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+ The model provides accurate geographic information with:
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+ - Precise coordinate data for all locations
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+ - Context-aware responses based on user queries
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+ - Natural language understanding of geographic concepts
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+ - Multi-level information retrieval (country → capital → landmarks)
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+
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+ ### Efficiency
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+ - 4-bit quantization for reduced memory footprint
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+ - MLX optimization for Apple Silicon performance
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+ - Async model loading for responsive user experience
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+ - Efficient geographic data structures for quick retrieval
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+
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+ ## Limitations
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+
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+ ### Current Limitations
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+ - Dataset limited to 10 countries and 30 landmarks
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+ - Requires specific model path configuration
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+ - Optimized for macOS with Apple Silicon
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+ - English language queries only
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+
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+ ### Geographic Coverage
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+ While the application includes major countries and landmarks, it does not represent a complete global dataset. Users should note that:
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+
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+ - Some countries and regions are not included
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+ - Landmark selection focuses on well-known tourist destinations
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+ - Coordinate precision varies based on source data
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+
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+ ## Ethical Considerations
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+
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+ ### Data Accuracy
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+ All geographic data has been verified from multiple sources, but users should:
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+ - Verify critical information from official sources
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+ - Understand that coordinates may have slight variations between sources
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+ - Recognize that some landmarks span large areas (e.g., Great Barrier Reef)
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+
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+ ### Privacy
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+ - The application does not collect user data
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+ - All processing happens locally when possible
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+ - No personal information is stored or transmitted
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+
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+ ## Future Improvements
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+
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+ Planned enhancements include:
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+ - Expanded geographic coverage to more countries
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+ - Additional landmark categories (natural wonders, historical sites)
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+ - Multi-language support
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+ - User-contributed data features
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+ - Advanced visualization options (3D maps, time-based data)
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+ - Integration with real-time geographic data sources
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+
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+ ## Citation
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+
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+ If you use this model in your research or projects, please cite:
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+
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+ ```bibtex
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+ @software{world_explorer_deepseek_2025,
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+ title = {World Explorer with DeepSeek AI},
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+ author = {Rivera, Martin},
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+ year = {2025},
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+ url = {https://huggingface.co/mlx-community/DeepSeek-V3.1-4bit},
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+ note = {Integration of MLX-optimized DeepSeek with Dash and Folium}
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+ }
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+ ```
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+
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+ ## License
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+
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+ This project integrates multiple components with different licenses:
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+
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+ - **DeepSeek Model**: Subject to DeepSeek's model license terms
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+ - **Dash**: MIT License
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+ - **Folium**: MIT License
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+ - **Application Code**: MIT License
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+
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+ Users should review and comply with all respective license terms.
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+
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+ ## Contact
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+
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+
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+ For questions about the DeepSeek model:
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+ - Hugging Face: [mlx-community/DeepSeek-V3.1-4bit](https://huggingface.co/mlx-community/DeepSeek-V3.1-4bit)
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+
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+ ## Acknowledgements
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+
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+ This project builds upon:
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+ - DeepSeek AI for the language model capabilities
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+ - MLX community for Apple Silicon optimization
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+ - Plotly for the Dash framework
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+ - Python Folium library for geographic visualization
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+ - OpenStreetMap for base map data
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+
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+ ---
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+
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+ *This model card was generated as part of the World Explorer with DeepSeek AI project to provide transparency about the capabilities, limitations, and appropriate use of this geographic AI application.*