Remove the reported success rate from the model card.

ASSET_SHA256SUMS

@@ -2,7 +2,7 @@ c485bd2ee62dbb1828eea5c5ea2bb7b0178f60d809329ebfd15bdf731f592f9a  action_vae.pt
 cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30  LICENSE
 07b1f41737ff5020427958e08e62c07a176ae395e39d7e41e1f237defa38378a  NOTICE
 b2cd77e9402b7897ba0d680eb45e4a38fb752e89641e3a9487a7cd4e947dad6c  policy.pt
-ac249dfcdb545e115f66c668effca365a9c72093ddc719dfbb68e85876f5c16c  README.md
+f12d3874b6bdcf25677f57c36a81e6586aab6d4228b6d2a572bd74fa5b852a9a  README.md
 835a23bad8ec61cf2c27c2f9440fe1f902ae5365c29f0c1858c0cb646e883594  stats/libero_10.json
 a648e545ad63d0d398ebf5735aa0e7426efdaf3fa55907c5ec50b72df6e273df  stats/libero_goal.json
 4eed60c361514c0f95f4ad24ec271972197e30463be07d82ec6c764cba3f6f83  stats/libero_object.json

README.md

@@ -14,7 +14,7 @@ tags:
 
 A latent world-action policy for the [LIBERO](https://github.com/Lifelong-Robot-Learning/LIBERO) benchmark, fine-tuned by Advanced Micro Devices, Inc. from [Wan2.2-TI2V-5B](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B).
 
-Each 32-step action chunk is encoded as 8 latent tokens of width 16. On the four LIBERO suites the policy reaches **97.2%** average success with a single sample.
+Each 32-step action chunk is encoded as 8 latent tokens of width 16.
 
 ## Files