| --- |
| license: mit |
| task_categories: |
| - image-to-image |
| - visual-document-retrieval |
| language: |
| - en |
| tags: |
| - retrieval |
| - multimodal |
| - composed-image-retrieval |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: pairs_img/train-*.parquet |
| --- |
| |
| # ret-sample — reasoning-retrieval query→positive pairs |
|
|
| Composed-image-retrieval (CIR) style pairs: a **query image + instruction** retrieves a |
| **target image**. Images are embedded directly in the parquet, so nothing external is needed |
| to train or browse. |
|
|
| - **3,127 pairs** · 8 shards · **341 MB** |
| - Built for [`williamium3000/Qwenvl2d5`](https://github.com/williamium3000/Qwenvl2d5) |
| (`ret-streaming-retsample` branch) and streamable by it with no S3 credentials. |
|
|
| ## Columns |
| | column | type | meaning | |
| |---|---|---| |
| | `q_image` | `Image()` | query image (PIL on access; stored as original JPEG bytes) | |
| | `pos_image` | `Image()` | positive/target image | |
| | `instruction` | string | the query instruction (what to retrieve) | |
| | `caption` | string | caption of the positive | |
| | `q_key`, `pos_key` | string | `blake3(raw file bytes)[:16]` content ids | |
| | `group_id` | int | near-duplicate cluster id (teacher cosine ≥ 0.98) | |
| | `n_text_tokens` | int | exact instruction length, Qwen2.5-VL tokenizer | |
| | `task`, `subset` | string | `cir`; source subset (results / instruct / …) | |
|
|
| ## Usage |
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("Icey444/ret-sample", split="train") |
| r = ds[0] |
| r["q_image"] # PIL.Image |
| r["instruction"] # "What would I need to use to navigate through a place like this?" |
| r["pos_image"] # PIL.Image |
| ``` |
|
|
| Training (in the repo above): |
| ```bash |
| bash scripts/sft_ret_sample_streaming.sh # --dataset ret_sample%100 |
| ``` |
|
|
| ## Notes |
| - **No hard negatives.** The training code uses in-batch InfoNCE; its collator explicitly |
| cannot take a 3rd item per instance, so mined negatives would be carried and never read. |
| - Images are stored **undecoded** and decoded to PIL once at preprocess time — lossless |
| (verified byte-identical through the pipeline) and no per-epoch re-encode. |
| - Source images originate from `jeffrey/reasoning_retrieval` on the zillion2 store; the |
| `_key` columns are content hashes of those exact bytes. |
|
|
