| --- |
| license: apache-2.0 |
| language: |
| - en |
| pretty_name: GIT SCRAPED |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
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| # 🚀 SKT-NRS / GIT-SCRAPED |
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| This repository is dedicated to hosting structural, curated, and diverse datasets—including GitHub roadmaps,and Roadmaps.sh Sites system architectures, technical diagrams, and mass scraped assets. |
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| Our ultimate mission is to fuel the development of next-generation **Sovereign Indian Intelligence** base models with high-fidelity, production-grade text-image structures. |
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| --- |
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| ## 📂 Repository Structure |
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| All the raw and structured crawled data is systematically hosted inside the primary ingestion folder: |
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| ```text |
| SKT-NRS/GIT-SCRAPED/ |
| └── 📁 SCRAPED-DATA/ # Core production folder for incoming bulk assets |
| ├── 📁 images # Extracted markdown, charts, and sequence text files |
| ├── 📁 texts # Architecture flowcharts and structural diagrams |
| └── 📁 Zip For Directly Download # Added To Directly Download |
| |
| ``` |
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|
| ### Phase 1: Recovery & Synchronization (Current Phase) |
| * **Status:** In Progress ⚙️ |
| * Re-extracting and consolidating the initial layout of **1200+ technical images** and web roadmaps. |
| * Synchronizing local automated dumps directly from cloud compute grids straight into the SCRAPED-DATA perimeter using multi-threaded chunk uploads. |
| ### Phase 2: Mass Scaling |
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| * **Status:** Planned 🎯 |
| * Transitioning away from standard element-level frontend scraping to heavy backend **API Sniffing and Open-Source Bulk Dump Data Ingestion**. |
| * Integrating multi-threaded pipelines via img2dataset to pool millions of high-resolution aesthetic and architectural data pairs. |
| * Curating specialized technical infographics, programming flowcharts, and system layout pipelines for multi-modal training. |
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| ### Phase 3: Public Sharing & Open Exchange |
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| * **Status:** Continuous 🌐 |
| * Opening the repository splits to the public and AI community. |
| * Actively facilitating a collaborative data ecosystem: developers can securely pull curated roadmaps from here while contributing back fresh token pairs to accelerate open-source AI growth. |
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| ## 🛠️ How to Load This Dataset |
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| You can easily pull the data down to your local cluster or cloud server using the Hugging Face datasets library: |
| ```python |
| from datasets import load_dataset |
| |
| # Load the entire scraped dataset pipeline |
| dataset = load_dataset("SKT-NRS/GIT-SCRAPED", data_files="SCRAPED-DATA/**") |
| |
| # Inspect the structure |
| print(dataset) |
| |
| ``` |
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