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--- |
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viewer: false |
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tags: [uv-script] |
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--- |
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# 🗺️ Atlas Export - One-Click Embedding Visualizations |
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Generate and deploy interactive embedding visualizations to HuggingFace Spaces with a single command. |
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## Quick Start |
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```bash |
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# Create a Space from any text dataset |
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uv run atlas-export.py stanfordnlp/imdb --space-name my-imdb-viz |
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# Your Space will be live at: |
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# https://huggingface.co/spaces/YOUR_USERNAME/my-imdb-viz |
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``` |
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## Examples |
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### Image Datasets |
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```bash |
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# Visualize image datasets with CLIP |
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uv run atlas-export.py \ |
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beans \ |
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--space-name bean-disease-atlas \ |
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--image-column image \ |
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--model openai/clip-vit-base-patch32 |
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``` |
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### Custom Embeddings |
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```bash |
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# Use a specific embedding model |
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uv run atlas-export.py \ |
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wikipedia \ |
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--space-name wiki-viz \ |
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--model nomic-ai/nomic-embed-text-v1.5 \ |
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--text-column text \ |
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--sample 50000 |
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``` |
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### Pre-computed Embeddings |
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```bash |
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# If you already have embeddings in your dataset |
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uv run atlas-export.py \ |
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my-dataset-with-embeddings \ |
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--space-name my-viz \ |
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--no-compute-embeddings \ |
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--x-column umap_x \ |
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--y-column umap_y |
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``` |
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### GPU Acceleration (HF Jobs) |
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```bash |
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# First, get your HF token (if not already set) |
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python -c "from huggingface_hub import get_token; print(get_token())" |
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# Run on HF Jobs with GPU using experimental UV support |
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hf jobs uv run --flavor t4-small \ |
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-s HF_TOKEN=your-token-here \ |
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https://huggingface.co/datasets/uv-scripts/build-atlas/raw/main/atlas-export.py \ |
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stanfordnlp/imdb \ |
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--space-name imdb-viz \ |
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--model sentence-transformers/all-mpnet-base-v2 \ |
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--sample 10000 |
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``` |
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Note: Replace `your-token-here` with your actual token. Available GPU flavors: `t4-small`, `t4-medium`, `l4x1`, `a10g-small`. |
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## Key Options |
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| Option | Description | Default | |
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|--------|-------------|---------| |
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| `dataset_id` | HuggingFace dataset to visualize | Required | |
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| `--space-name` | Name for your Space | Required | |
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| `--model` | Embedding model to use | Auto-selected | |
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| `--text-column` | Column containing text | "text" | |
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| `--image-column` | Column containing images | None | |
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| `--sample` | Number of samples to visualize | All | |
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| `--split` | Dataset split to use | "train" | |
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| `--local-only` | Generate locally without deploying | False | |
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| `--output-dir` | Local output directory | Temp dir | |
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| `--hf-token` | HuggingFace API token | From env/CLI | |
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Run without arguments to see all options and more examples. |
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## How It Works |
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1. Loads dataset from HuggingFace Hub |
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2. Generates embeddings (or uses pre-computed) |
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3. Creates static web app with embedded data |
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4. Deploys to HF Space |
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The resulting visualization runs entirely in the browser using WebGPU acceleration. |
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## Credits |
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Built on [Embedding Atlas](https://github.com/apple/embedding-atlas) by Apple. See the [documentation](https://apple.github.io/embedding-atlas/) for more details about the underlying technology. |
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--- |
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Part of the [UV Scripts](https://huggingface.co/uv-scripts) collection 🚀 |
