Update README.md

README.md

@@ -18,7 +18,7 @@ configs:
 - config_name: default
   data_files:
   - split: train
-    path: data_manifest.csv
+    path: data_manifest.csva
 ---
 
 # LM-SimBench
@@ -29,21 +29,15 @@ LM-SimBench is a large-scale training-performance profiling dataset for large la
 
 Each model is sampled under feasible combinations of data parallelism (DP), tensor parallelism (TP), pipeline parallelism (PP), context parallelism (CP), expert parallelism (EP, for MoE models), and recomputation settings. The released files contain structured CSV records for iteration time, rank-level peak memory, operator latency, communication behavior, and matrix-operator hardware characteristics.
 
-The original raw dataset is available at [jiujiudahaozi/LM-SimBench_row](https://huggingface.co/datasets/anonymous-neurips26-ljasd/LM-SimBench_row). This repository publishes the organized CSV dataset for downstream performance modeling and analysis.
+The original raw dataset is available at [jiujiudahaozi/LM-SimBench_row](https://huggingface.co/datasets/anonymous-neurips26-ljasd/LM-SimBench_raw). This repository publishes the organized CSV dataset for downstream performance modeling and analysis.
 
 This dataset is ready for research use. Commercial use should follow the license and terms below.
 
-## Dataset Owner(s)
 
-jiujiudahaozi
-
-## Dataset Creation Date
-
-Created on: May 1, 2026
 
 ## License/Terms of Use
 
-This dataset is governed by the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).
+This dataset is governed by the Creative Commons Attribution 4.0 International License (CC BY 4.0).
 
 Users may share and adapt the dataset, including for commercial purposes, provided that appropriate attribution is given and derived datasets are distributed under the same license. Please cite this dataset and keep a reference to the original raw-data repository when redistributing derivative versions.