---
pretty_name: MS MARCO v1 Passage multivector embeddings (ColBERTv2)
task_categories: [text-retrieval]
tags: [late-interaction, colbert, multivector, msmarco]
---

# MS MARCO v1 Passage, ColBERTv2

Token-level (late-interaction) ColBERTv2 embeddings of the MS MARCO v1 passage collection and the dev/small queries.

## Source
- Collection: MS MARCO v1 passage (`ir_datasets` `msmarco-passage`), 8,841,823 passages
- Queries: dev/small, 6,980 queries and 7,437 qrels (`msmarco-passage/dev/small`)
- Document order: passage id order (row *i* is pid *i*)

## Encoding
- Model: ColBERTv2 (`colbert-ir/colbertv2.0`, BERT-base-uncased tokenizer)
- Documents start with `[CLS]` and the ColBERT `[D]` marker (token id 2)
- Queries: always 32 vectors (`[MASK]` expansion, no zero padding)
- Vectors: 128-d, L2-normalized
- **Not recorded:** exact checkpoint revision, encoding library, document length cap (the longest document has 300 vectors), and whether punctuation was dropped

## Statistics
| | |
|---|---|
| Token vectors (N) | 597,909,919 |
| Avg vectors per document | 67.6 (min 4, max 300) |
| Vectors per query | 32 |

## Files
| File | dtype | Shape | Content |
|---|---|---|---|
| `documents.npy` | uint16 (`<u2`) | `[597909919, 128]` | Raw float16 bit patterns stored as uint16. Read with `.view(np.float16)` |
| `doclens.npy` | int32 | `[8841823]` | Vectors per document; `sum == N` |
| `token_ids_per_token.npy` | int64 | `[597909919]` | Input token id of each row of `documents.npy` |
| `doc_ids.npy` | int64 | `[8841823]` | MS MARCO pid (equals the row index) |
| `queries.npy` | float32 | `[6980, 32, 128]` | Query vectors |
| `queries_ids.npy` | int64 | `[6980]` | MS MARCO qid of each query |

Document ids are MS MARCO passage ids and equal the row index: row *i* of `doclens.npy` is passage *i*.

`documents.npy` stores float16 values as their raw 16-bit patterns, with dtype uint16.
In numpy, read it with `np.load("documents.npy", mmap_mode="r").view(np.float16)`.

## Relevance judgments
The official MS MARCO passage dev/small qrels (`qrels.dev.small.tsv`): 7,437 relevant
query-passage pairs over the 6,980 queries, all with relevance 1 (`ir_datasets` `msmarco-passage/dev/small`).
Standard metric: MRR@10 (`RR@10` in `ir_measures`).