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README.md

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+---
+language:
+- en
+license: apache-2.0
+size_categories:
+- 1M<n<10M
+pretty_name: MMEB-train-lance
+tags:
+- embedding
+- lance
+- multimodal
+---
+
+# MMEB Training Dataset (Lance Format)
+
+This is a **Lance-format** version of the [TIGER-Lab/MMEB-train](https://huggingface.co/datasets/TIGER-Lab/MMEB-train) dataset, optimized for efficient storage and fast random access.
+
+The original dataset is used for training VLM2Vec models in the paper [VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks](https://arxiv.org/abs/2410.05160) (ICLR 2025).
+
+## Why Lance Format?
+
+| Metric | Original (Parquet + Images) | Lance |
+|--------|----------------------------|-------|
+| Storage Size | 94 GB | 47 GB (**-50%**) |
+| File Count | 1,353,735 | 252 (**-99.98%**) |
+| Random Access | Slow (many small files) | Fast (columnar + indexed) |
+
+## Directory Structure
+
+```
+TIGER-Lab_MMEB-train/
+└── data/
+    ├── A-OKVQA/
+    │   ├── train.lance/        # Training metadata
+    │   ├── original.lance/     # Original instructions
+    │   └── diverse.lance/      # Diverse instructions
+    ├── MSCOCO/
+    │   └── ...
+    └── images/
+        ├── A-OKVQA.lance/      # Images (binary)
+        ├── MSCOCO.lance/
+        └── ...
+```
+
+## Schema
+
+### Metadata (`{dataset}/{variant}.lance`)
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `qry` | string | Query text (may contain `<\|image_1\|>` placeholder) |
+| `qry_image_id` | string | Query image path (empty if text-only) |
+| `pos_text` | string | Positive sample text |
+| `pos_image_id` | string | Positive sample image path |
+| `neg_text` | string | Negative sample text (optional) |
+| `neg_image_id` | string | Negative sample image path (optional) |
+
+### Images (`images/{dataset}.lance`)
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `image_id` | string | Image path identifier |
+| `data` | binary | Image binary data (JPEG) |
+
+## Usage
+
+```python
+import lance
+
+# Load metadata
+metadata = lance.dataset("TIGER-Lab_MMEB-train/data/A-OKVQA/train.lance")
+df = metadata.to_table().to_pandas()
+
+# Load images
+images = lance.dataset("TIGER-Lab_MMEB-train/data/images/A-OKVQA.lance")
+
+# Create index for fast lookup (optional, one-time)
+images.create_scalar_index("image_id", "BTREE")
+
+# Query image by ID
+result = images.to_table(
+    filter="image_id = 'images/A-OKVQA/Train/A-OKVQA_image_0.jpg'"
+)
+image_bytes = result["data"][0].as_py()
+
+# Batch query
+ids = ["images/A-OKVQA/Train/A-OKVQA_image_0.jpg",
+       "images/A-OKVQA/Train/A-OKVQA_image_1.jpg"]
+in_clause = ", ".join([f"'{id}'" for id in ids])
+result = images.to_table(filter=f"image_id IN ({in_clause})")
+```
+
+## Dataset Statistics
+
+| Dataset | Samples | Images |
+|---------|---------|--------|
+| A-OKVQA | 17,056 | 17,056 |
+| ChartQA | 28,299 | 28,299 |
+| CIRR | 26,116 | 16,640 |
+| DocVQA | 39,463 | 39,463 |
+| HatefulMemes | 8,500 | 8,500 |
+| ImageNet_1K | 100,000 | 100,000 |
+| InfographicsVQA | 23,946 | 4,406 |
+| MSCOCO | 100,000 | 59,969 |
+| MSCOCO_i2t | 113,287 | 113,287 |
+| MSCOCO_t2i | 100,000 | 70,414 |
+| N24News | 48,988 | 48,988 |
+| NIGHTS | 15,941 | 31,882 |
+| OK-VQA | 9,009 | 9,009 |
+| SUN397 | 19,850 | 19,850 |
+| VisDial | 123,287 | 123,287 |
+| Visual7W | 69,817 | 14,366 |
+| VisualNews_i2t | 100,000 | 100,000 |
+| VisualNews_t2i | 99,903 | 99,903 |
+| VOC2007 | 7,844 | 7,844 |
+| WebQA | 17,166 | 12,873 |
+
+Each dataset has 3 variants: `train`, `original`, and `diverse` (same sample count, different instruction templates).
+
+## Original Dataset
+
+This dataset is derived from [TIGER-Lab/MMEB-train](https://huggingface.co/datasets/TIGER-Lab/MMEB-train). For evaluation, please refer to [TIGER-Lab/MMEB-eval](https://huggingface.co/datasets/TIGER-Lab/MMEB-eval).
+
+## Citation
+
+```bibtex
+@article{jiang2024vlm2vec,
+  title={VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks},
+  author={Jiang, Ziyan and Meng, Rui and Yang, Xinyi and Yavuz, Semih and Zhou, Yingbo and Chen, Wenhu},
+  journal={arXiv preprint arXiv:2410.05160},
+  year={2024}
+}
+```
+
+## License
+
+Apache-2.0 (same as the original dataset)