Dataset card organized by task

README.md

@@ -1,7 +1,7 @@
 ---
 license: other
 license_name: per-source-terms
-pretty_name: Instruct-181K
+pretty_name: Instruct-180K
 language:
 - en
 size_categories:
@@ -10,6 +10,10 @@ task_categories:
 - visual-question-answering
 - any-to-any
 configs:
+- config_name: birds_eye_view_rotation
+  data_files:
+  - split: train
+    path: preview/birds_eye_view_rotation.parquet
 - config_name: panoramic_completion
   data_files:
   - split: train
@@ -30,10 +34,6 @@ configs:
   data_files:
   - split: train
     path: preview/object_rotation.parquet
-- config_name: birds_eye_view_rotation
-  data_files:
-  - split: train
-    path: preview/birds_eye_view_rotation.parquet
 - config_name: object_orientation
   data_files:
   - split: train
@@ -76,9 +76,9 @@ configs:
     path: preview/birds_eye_view.parquet
 ---
 
-# Instruct-181K
+# Instruct-180K
 
-Instruct-181K is the instruction-tuning data of
+Instruct-180K is the instruction-tuning data of
 [ThinkMorph-SSL-Instruct](https://huggingface.co/ThinkMorph/ThinkMorph-SSL-Instruct), trained from
 [ThinkMorph-SSL-Base](https://huggingface.co/ThinkMorph/ThinkMorph-SSL-Base). It holds 180,490 interleaved reasoning
 traces. Each trace has a question, one or more input images, reasoning text with intermediate
@@ -126,9 +126,9 @@ All rows are training rows. Choose a task in the Dataset Viewer to see examples.
 ## Download
 
 ```bash
-hf download ThinkMorph/Instruct-181K --repo-type dataset --include "shards/*" --local-dir Instruct-181K
+hf download ThinkMorph/Instruct-180K --repo-type dataset --include "shards/*" --local-dir Instruct-180K
 mkdir -p data
-for f in Instruct-181K/shards/*.tar; do tar -xf "$f" -C data; done
+for f in Instruct-180K/shards/*.tar; do tar -xf "$f" -C data; done
 ```
 
 - `shards/SHARDS.json` gives each shard's SHA256, and `MANIFEST.json` each extracted file's.
@@ -156,6 +156,28 @@ data/
 - `options` appears only in tasks that keep the choices outside the question.
 - Image paths are relative to the row's file. `id` is a stable public id.
 
+## Reading the data
+
+A trace reads in this order: the input images and the question, then
+`reasoning_thought_0`, `reasoning_image_0`, `reasoning_thought_1`, and so on, then the answer.
+
+```python
+import json
+from pathlib import Path
+from PIL import Image
+
+folder = Path("data/bbox")                      # one task folder of the extracted release
+with open(folder / "train.jsonl") as f:
+    row = json.loads(next(f))
+inputs = [Image.open(folder / p) for p in row["images"]]
+steps, i = [], 0
+while f"reasoning_thought_{i}" in row:
+    image = row.get(f"reasoning_image_{i}")
+    steps.append((row[f"reasoning_thought_{i}"], Image.open(folder / image) if image else None))
+    i += 1
+print(row["question"], row.get("options"), row["answer"])
+```
+
 ## Rows without images
 
 `text_only/` holds the rows of `panoramic_completion` whose images come from Matterport3D, and of `exo_to_ego` (Ego-Exo4D). It has the same task folders as the main release.