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git clone https://github.com/krishnakaushik195/desidataTools overview
# DesiData DesiData publishes India-focused datasets and tools for exploring and working with them. This repository contains dataset notebooks and examples for using DesiData data in Google Colab and Python. - **Website:** [desidata.in](https://www.desidata.in/) - **Browse datasets:** [DesiData datasets](https://www.desidata.in/datasets) - **Weekly model benchmark:** [DesiData Bench](https://www.desidata.in/bench) - **Community announcements and discussion:** [DesiData Community](https://www.desidata.in/community) - **Python package:** [desidata on PyPI](https://pypi.org/project/desidata/) ## Use a dataset notebook Open a notebook under [`notebooks/`](./notebooks/) and run it in Colab or your own Python environment. The notebook collection is refreshed as datasets are added. Some notebook download examples may need updating to use the current authenticated download flow. See [Download data with a DD token](#download-data-with-a-dd-token) before running a download cell. ## Download data with a DD token DesiData datasets are free. To associate programmatic downloads with your DesiData account, create a free DD token from your [DesiData profile](https://www.desidata.in/profile). 1. Sign in to DesiData and create a token in your profile. 2. Copy and save it when it is shown. Treat it like a password; do not paste it into a notebook that you share or commit it to GitHub. 3. Set it as the `DD_TOKEN` environment variable in your local environment, or add it to Colab's **Secrets** as `DD_TOKEN`. 4. Use the token in the DesiData Python package or authenticated download examples. For example, in a local terminal: ```bash # macOS or Linux export DD_TOKEN="your-token" ``` ```powershell # Windows PowerShell $env:DD_TOKEN = "your-token" ``` In Google Colab, add `DD_TOKEN` under the notebook's **Secrets** panel and grant the notebook access to it. Do not put the token directly in a notebook cell. A token is free. Authenticated download requests are associated with your account so DesiData can show download activity and counts. The count records a download request; it does not prove that a file finished downloading or was used. ## Weekly benchmark The DesiData benchmark page compares selected open models on the current benchmark set. The plan is to run and publish a refreshed model comparison each Saturday afternoon, using the latest DesiData benchmark data. Check [DesiData Bench](https://www.desidata.in/bench) for the current results and methodology. ## Updates This repository is a public place to follow notebook and data-access changes. New dated entries will be added here as the project changes. ### 2026-09-27 — DD token downloads Programmatic dataset downloads now use a free DD token linked to a DesiData account. This lets download activity be attributed to the account while keeping the datasets free. Create a token from your [profile](https://www.desidata.in/profile); never commit it to a notebook or repository. ### Planned — Weekly model benchmark The plan is to publish updated open-model benchmark results on Saturday afternoons. Results and details will be posted on the [benchmark page](https://www.desidata.in/bench). ## Contributing and feedback Have a dataset request, notebook correction, or benchmark suggestion? Open a GitHub issue or join the conversation on the [DesiData Community page](https://www.desidata.in/community). ## DesiData MCP plugin The [DesiData MCP plugin](plugins/desidata-mcp/) lets AI assistants search the published catalogue, inspect dataset metadata and provenance, preview a small sample, and get notebook or Python loader examples. Search and previews are read-only and do not need an account or API token. Full dataset downloads continue to use the user's own DesiData `DD_TOKEN` through the normal download flow. The same remote MCP service works with Cursor, Codex, and Gemini CLI. See the plugin [setup guide](plugins/desidata-mcp/README.md) for connection instructions and current limits. ### Install in Gemini CLI ```sh gemini extensions install https://github.com/krishnakaushik195/desidata ``` Restart Gemini CLI after installation, then run `/mcp list` to confirm DesiData is connected. Search and previews work without signing in; full dataset downloads use the user's own DesiData `DD_TOKEN` through the regular download flow.
What people ask about desidata
What is krishnakaushik195/desidata?
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krishnakaushik195/desidata is tools for the Claude AI ecosystem with 0 GitHub stars.
How do I install desidata?
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You can install desidata by cloning the repository (https://github.com/krishnakaushik195/desidata) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
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Our security agent has analyzed krishnakaushik195/desidata and assigned a Trust Score of 52/100 (tier: OK). See the full breakdown of passed checks and flags on this page.
Who maintains krishnakaushik195/desidata?
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krishnakaushik195/desidata is maintained by krishnakaushik195. The last recorded GitHub activity is dated 2026-10-09, with 0 open issues.
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Yes. On ClaudeWave you can browse similar tools at /categories/tools, sorted by popularity or recent activity.
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