Update README.md

README.md

@@ -37,61 +37,9 @@ test_ds = load_dataset("fesvhtr/FunQA", "standard", split="test")
 mcqa_ds = load_dataset("fesvhtr/FunQA", "mcqa", split="mcqa_test")
 ```
 
-## Load from Local Files
-
-```python
-from datasets import load_dataset
-
-standard_ds = load_dataset(
-    "parquet",
-    data_files={
-        "train": "data/train.parquet",
-        "validation": "data/validation.parquet",
-        "test": "data/test.parquet",
-    },
-)
-
-mcqa_ds = load_dataset(
-    "parquet",
-    data_files={"mcqa_test": "data/mcqa_test.parquet"},
-)
-```
-
-## Dataset Configs
-
-### `standard`
-
-Splits:
-
-- `train`
-- `validation`
-- `test`
-
-Columns:
-
-- `instruction`
-- `visual_input`
-- `output`
-- `task`
-
-### `mcqa`
-
-Splits:
-
-- `mcqa_test`
-
-Columns:
-
-- `instruction`
-- `visual_input`
-- `gt`
-- `id`
-
-
-
 ## Download Video Archives
 
-If you want the original video files, download the split archives explicitly from the dataset repository.
+For the video files, download the split archives explicitly from the dataset repository.
 
 Download one archive into the Hugging Face cache:
 
@@ -141,6 +89,57 @@ video_path = next(Path("videos/test").rglob(video_name))
 print(video_path)
 ```
 
+## Load from Local Files
+
+```python
+from datasets import load_dataset
+
+standard_ds = load_dataset(
+    "parquet",
+    data_files={
+        "train": "data/train.parquet",
+        "validation": "data/validation.parquet",
+        "test": "data/test.parquet",
+    },
+)
+
+mcqa_ds = load_dataset(
+    "parquet",
+    data_files={"mcqa_test": "data/mcqa_test.parquet"},
+)
+```
+
+## Dataset Configs
+
+### `standard`
+
+Splits:
+
+- `train`
+- `validation`
+- `test`
+
+Columns:
+
+- `instruction`
+- `visual_input`
+- `output`
+- `task`
+
+### `mcqa`
+
+Splits:
+
+- `mcqa_test`
+
+Columns:
+
+- `instruction`
+- `visual_input`
+- `gt`
+- `id`
+
+
 ## Notes
 
 - The parquet files preserve the original JSON field names.