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README.md

@@ -10,6 +10,7 @@ configs:
   data_files:
   - split: train
     path: data/msb_type.jsonl
+  default: true
 - config_name: et_type
   data_files:
   - split: train
@@ -18,7 +19,6 @@ configs:
   data_files:
   - split: train
     path: data/scicobench_all.jsonl
-  default: true
 ---
 
 # AInsteinBench
@@ -31,9 +31,9 @@ AInsteinBench contains 1,329 code generation problems from two sources:
 
 | Subset | Samples | Description |
 |--------|---------|-------------|
-| **msb_type** | 244 | Multi-SWE-bench scientific computing tasks |
+| **msb_type** | 244 | Multi-SWE-bench scientific computing tasks (default) |
 | **et_type** | 1,085 | Einstein Toolkit code completion tasks |
-| **scicobench_all** | 1,329 | Combined dataset in unified format (default) |
+| **scicobench_all** | 1,329 | Combined dataset in unified format |
 
 ### Data Sources
 
@@ -106,8 +106,8 @@ Data is formatted following the Multi-SWE-Bench structure with issue description
 ```python
 from datasets import load_dataset
 
-# Load the unified format (default)
-dataset = load_dataset("ByteDance-Seed/AInsteinBench", "scicobench_all")
+# Load the default subset (msb_type)
+dataset = load_dataset("ByteDance-Seed/AInsteinBench")
 
 # Load specific subsets
 et_dataset = load_dataset("ByteDance-Seed/AInsteinBench", "et_type")