VLABench/pi0-fast-primitive-10task

Model

0

stars

4

commits

2

linked in READMEs

Nov 11, 2025

updated

README

Pi0-fast official implementation trained on VLABench datasets.

This repository provides the official release of the Pi0-fast model trained with the whole VLABench's official primitive tasks dataset. To be noticed, this config corresponds to the relative chunk.

Evaluation

To run this checkpoint, please clone this repo: https://github.com/Shiduo-zh/openpi, and checkout to the branch main. Assume that you download this checkpoints and put it in the directory checkpoints, to run the policy as server, please run:

bash vla_bench_scipts/serve_policy.sh pifast_ft_vlabench_primitive checkpoints/VLABench/pi0-fast-primitive-10task/29999/

After serving the policy, open another terminal and run:

bash vla_bench_scipts/multi_run_vlabench.sh <Your path to store the evaluate results>

Train

To reproduce the training result, please run the training script with the config pifast_ft_vlabench_primitive.

XLA_PYTHON_CLIENT_MEM_FRACTION=0.95 uv run scripts/train.py pifast_ft_vlabench_primitive --exp-name=pi0_ft_vlabench_primitive --overwrite

Our checkpoint is trained on 8 H100 for 30k iterations, with 5000 episodes data acrossing 10 tasks.

Reference Results

The reference success rate of this model is:

Trackadd_condimentinsert_flowerselect_bookselect_chemistry_tubeselect_drinkselect_fruitselect_mahjongselect_paintingselect_pokerselect_toyAvg_SR
track_1_in_distribution0.420.040.280.160.0820.380.240.480.580.240.291
track_2_cross_category0.04?0.1840.080.120.320.100.46?0.140.181
track_3_common_sense0.32?0.280.240.10.320.020.36?0.140.211
track_4_semantic_instruction0.24?0.170.140.120.320.120.44?0.10.199
track_6_unseen_texture0.42?0.340.10.10.260.180.38?0.120.236

Contributors

CyberDJ

4 commits

VLABench/pi0-fast-primitive-10task

Model

0

stars

4

commits

2

linked in READMEs

Nov 11, 2025

updated

README

Pi0-fast official implementation trained on VLABench datasets.

This repository provides the official release of the Pi0-fast model trained with the whole VLABench's official primitive tasks dataset. To be noticed, this config corresponds to the relative chunk.

Evaluation

To run this checkpoint, please clone this repo: https://github.com/Shiduo-zh/openpi, and checkout to the branch main. Assume that you download this checkpoints and put it in the directory checkpoints, to run the policy as server, please run:

bash vla_bench_scipts/serve_policy.sh pifast_ft_vlabench_primitive checkpoints/VLABench/pi0-fast-primitive-10task/29999/

After serving the policy, open another terminal and run:

bash vla_bench_scipts/multi_run_vlabench.sh <Your path to store the evaluate results>

Train

To reproduce the training result, please run the training script with the config pifast_ft_vlabench_primitive.

XLA_PYTHON_CLIENT_MEM_FRACTION=0.95 uv run scripts/train.py pifast_ft_vlabench_primitive --exp-name=pi0_ft_vlabench_primitive --overwrite

Our checkpoint is trained on 8 H100 for 30k iterations, with 5000 episodes data acrossing 10 tasks.

Reference Results

The reference success rate of this model is:

Trackadd_condimentinsert_flowerselect_bookselect_chemistry_tubeselect_drinkselect_fruitselect_mahjongselect_paintingselect_pokerselect_toyAvg_SR
track_1_in_distribution0.420.040.280.160.0820.380.240.480.580.240.291
track_2_cross_category0.04?0.1840.080.120.320.100.46?0.140.181
track_3_common_sense0.32?0.280.240.10.320.020.36?0.140.211
track_4_semantic_instruction0.24?0.170.140.120.320.120.44?0.10.199
track_6_unseen_texture0.42?0.340.10.10.260.180.38?0.120.236

Contributors

CyberDJ

4 commits