WIP: Add dataset card with DuckDB query examples (demo only)

README.md

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+---
+dataset_info:
+  - config_name: bioclip-2_float16
+    features:
+      - name: uuid
+        dtype: string
+      - name: kingdom
+        dtype: string
+      - name: phylum
+        dtype: string
+      - name: class
+        dtype: string
+      - name: order
+        dtype: string
+      - name: family
+        dtype: string
+      - name: genus
+        dtype: string
+      - name: species
+        dtype: string
+      - name: img_type
+        dtype: string
+      - name: basisOfRecord
+        dtype: string
+      - name: publisher
+        dtype: string
+      - name: identifier
+        dtype: string
+      - name: emb
+        sequence: float16
+        length: 768
+    splits:
+      - name: train
+        num_examples: 239580103
+configs:
+  - config_name: bioclip-2_float16
+    data_files:
+      - split: train
+        path: bioclip-2_float16/*.parquet
+license: mit
+---
+
+# TreeOfLife-200M Embeddings
+
+> **Work in progress** — this dataset card is under active development.
+
+239 million BioCLIP 2 embeddings (768-dim, float16) for [TreeOfLife-200M](https://huggingface.co/datasets/imageomics/TreeOfLife-200M) images, sorted by taxonomic hierarchy. We recommend using [DuckDB](https://duckdb.org/) to access this dataset.
+
+## Query Remotely
+
+Query directly from HuggingFace without downloading anything. DuckDB uses Parquet page indexes to skip irrelevant files, making filtered queries fast over the network.
+
+> `order` and `class` are SQL reserved words — always quote them as `"order"` and `"class"`.
+
+### Python
+
+```python
+import duckdb
+
+con = duckdb.connect()
+# Authenticate for higher rate limits (recommended)
+con.execute("CREATE SECRET (TYPE HUGGINGFACE, TOKEN 'hf_...')")
+
+glob = "hf://datasets/imageomics/TreeOfLife-200M-Embeddings/bioclip-2_float16/*.parquet"
+
+# Get all embeddings for a species
+df = con.sql(f"""
+    SELECT uuid, emb
+    FROM read_parquet('{glob}')
+    WHERE species = 'Danaus plexippus'
+""").df()
+
+# Count by taxonomic order
+con.sql(f"""
+    SELECT "order", COUNT(*) as n
+    FROM read_parquet('{glob}')
+    WHERE "order" IS NOT NULL
+    GROUP BY "order"
+    ORDER BY n DESC
+    LIMIT 10
+""").show()
+
+# Filter by family
+con.sql(f"""
+    SELECT genus, species, COUNT(*) as n
+    FROM read_parquet('{glob}')
+    WHERE family = 'Felidae'
+    GROUP BY genus, species
+    ORDER BY n DESC
+    LIMIT 10
+""").show()
+```
+
+### CLI
+
+```bash
+# Install DuckDB: https://duckdb.org/docs/installation
+# Then query directly from the command line:
+
+duckdb -c "
+    SELECT species, COUNT(*) as n
+    FROM read_parquet('hf://datasets/imageomics/TreeOfLife-200M-Embeddings/bioclip-2_float16/*.parquet')
+    WHERE family = 'Nymphalidae'
+    GROUP BY species
+    ORDER BY n DESC
+    LIMIT 10;
+"
+```
+
+## Download a Taxonomic Slice
+
+Instead of downloading the full 331 GB dataset, extract only the taxa you need. The sorted data and page indexes ensure only the relevant row groups are fetched over the network.
+
+### Python
+
+```python
+import duckdb
+
+con = duckdb.connect()
+con.execute("CREATE SECRET (TYPE HUGGINGFACE, TOKEN 'hf_...')")
+
+glob = "hf://datasets/imageomics/TreeOfLife-200M-Embeddings/bioclip-2_float16/*.parquet"
+
+# Save a single family to a local file
+con.sql(f"""
+    COPY (
+        SELECT * FROM read_parquet('{glob}')
+        WHERE family = 'Felidae'
+    ) TO 'felidae.parquet'
+""")
+
+# Now query locally — instant
+con.sql("SELECT species, COUNT(*) as n FROM 'felidae.parquet' GROUP BY species ORDER BY n DESC").show()
+```
+
+### CLI
+
+```bash
+duckdb -c "
+    COPY (
+        SELECT * FROM read_parquet('hf://datasets/imageomics/TreeOfLife-200M-Embeddings/bioclip-2_float16/*.parquet')
+        WHERE \"order\" = 'Primates'
+    ) TO 'primates.parquet';
+"
+```
+
+| Slice Example | Rows | Size | Time |
+|---------------|------|------|------|
+| Species: *Danaus plexippus* | 299,874 | 913 MB | ~1 min* |
+| Family: Felidae | 149,890 | 457 MB | ~1 min* |
+| Order: Primates | 160,307 | 489 MB | ~1 min* |
+
+*\*First query in a session includes a one-time ~3 min glob resolution overhead: DuckDB expands the `*.parquet` wildcard by making HTTP requests to HuggingFace to discover all 685 filenames. Subsequent queries in the same session reuse the cached file list.*
+
+## Download Everything
+
+For full-dataset analytics, download all files first.
+
+```bash
+huggingface-cli download imageomics/TreeOfLife-200M-Embeddings \
+  --repo-type dataset --include "bioclip-2_float16/*" --local-dir ./data
+```
+
+```bash
+duckdb -c "
+    SELECT \"order\", COUNT(*) as n
+    FROM read_parquet('./data/bioclip-2_float16/*.parquet')
+    WHERE \"order\" IS NOT NULL
+    GROUP BY \"order\"
+    ORDER BY n DESC
+    LIMIT 10;
+"
+```
+
+## Schema
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `uuid` | `string` | Unique image identifier |
+| `kingdom` | `string` | Taxonomic kingdom |
+| `phylum` | `string` | Taxonomic phylum |
+| `class` | `string` | Taxonomic class |
+| `order` | `string` | Taxonomic order |
+| `family` | `string` | Taxonomic family |
+| `genus` | `string` | Taxonomic genus |
+| `species` | `string` | Taxonomic species |
+| `img_type` | `string` | Image source type |
+| `basisOfRecord` | `string` | Basis of record |
+| `publisher` | `string` | Data publisher |
+| `identifier` | `string` | Source URI |
+| `emb` | `fixed_size_list<float16>[768]` | BioCLIP 2 embedding |
+
+## Data Organization
+
+- **Sort order:** `kingdom > phylum > class > order > family > genus > species`
+- **Row groups:** 50,000 rows each with column statistics and page indexes
+- **Compression:** ZSTD level 3
+- **Precision:** float16 (lossless cosine similarity vs float32 source)
+
+## Configs
+
+| Config | Model | Precision | Files | Size | Rows |
+|--------|-------|-----------|-------|------|------|
+| `bioclip-2_float16` | BioCLIP 2 | float16 | 685 | 331 GB | 239,580,103 |