README.md

# 🗺️ Atlas Export - One-Click Embedding Visualizations

Generate and deploy interactive embedding visualizations to HuggingFace Spaces with a single command.

## Quick Start

```bash
# Create a Space from any text dataset
uv run atlas-export.py stanfordnlp/imdb --space-name my-imdb-viz

# Your Space will be live at:
# https://huggingface.co/spaces/YOUR_USERNAME/my-imdb-viz
```

## Examples

### Image Datasets

```bash
# Visualize image datasets with CLIP
uv run atlas-export.py \
    beans \
    --space-name bean-disease-atlas \
    --image-column image \
    --model openai/clip-vit-base-patch32
```

### Custom Embeddings

```bash
# Use a specific embedding model
uv run atlas-export.py \
    wikipedia \
    --space-name wiki-viz \
    --model nomic-ai/nomic-embed-text-v1.5 \
    --text-column text \
    --sample 50000
```

### Pre-computed Embeddings

```bash
# If you already have embeddings in your dataset
uv run atlas-export.py \
    my-dataset-with-embeddings \
    --space-name my-viz \
    --no-compute-embeddings \
    --x-column umap_x \
    --y-column umap_y
```

### GPU Acceleration

```bash
# Run on HF Jobs with GPU for faster embedding generation
hf jobs run vllm/vllm-openai:latest --flavor t4-small \
    -s HF_TOKEN=$HF_TOKEN \
    uv run https://huggingface.co/datasets/uv-scripts/build-atlas/raw/main/atlas-export.py \
    stanfordnlp/imdb \
    --space-name imdb-viz \
    --model sentence-transformers/all-mpnet-base-v2 \
    --sample 10000
```

## Key Options

| Option | Description | Default |
|--------|-------------|---------|
| `dataset_id` | HuggingFace dataset to visualize | Required |
| `--space-name` | Name for your Space | Required |
| `--model` | Embedding model to use | Auto-selected |
| `--text-column` | Column containing text | Auto-detected |
| `--image-column` | Column containing images | None |
| `--sample` | Number of samples to visualize | All |
| `--local-only` | Generate locally without deploying | False |
| `--output-dir` | Local output directory | Temp dir |

Run without arguments to see all options and more examples.

## How It Works

1. Loads dataset from HuggingFace Hub
2. Generates embeddings (or uses pre-computed)
3. Creates static web app with embedded data
4. Deploys to HF Space

The resulting visualization runs entirely in the browser using WebGPU acceleration.

## Credits

Built on [Embedding Atlas](https://github.com/apple/embedding-atlas) by Apple.

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Part of the [UV Scripts](https://huggingface.co/uv-scripts) collection 🚀