Downloads · 30 days
7
8% of all-time downloads
groot_fft_10000steps_ga4_real_0_put_bowl
continuallearning/groot_fft_10000steps_ga4_real_0_put_bowl
groot_fft_10000steps_ga4_real_0_put_bowl is a robotics model from continuallearning. Use it for the robotics task on the model card, and read the license before you ship it in a product. It is set up for lerobot. The card lists the license as apache-2.0.
Model type not recognized — please update this template.
All-time downloads
92
Public
Parameters
2.7B
5.4 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors5.4 GB · 100%
At a glance
- Task
- Robotics
- Library
- lerobot
- License
- apache-2.0
- Access
- Public
- Created
- Mar 12, 2026
- Updated
- Mar 12, 2026
- SHA
- 9b2ee12e
Model card
From the Hugging Face model README
Model Card for groot
<!-- Provide a quick summary of what the model is/does. -->Model type not recognized — please update this template.
This policy has been trained and pushed to the Hub using LeRobot. See the full documentation at LeRobot Docs.
How to Get Started with the Model
For a complete walkthrough, see the training guide. Below is the short version on how to train and run inference/eval:
Train from scratch
lerobot-train \
--dataset.repo_id=${HF_USER}/<dataset> \
--policy.type=act \
--output_dir=outputs/train/<desired_policy_repo_id> \
--job_name=lerobot_training \
--policy.device=cuda \
--policy.repo_id=${HF_USER}/<desired_policy_repo_id>
--wandb.enable=true
Writes checkpoints to outputs/train/<desired_policy_repo_id>/checkpoints/.
Evaluate the policy/run inference
lerobot-record \
--robot.type=so100_follower \
--dataset.repo_id=<hf_user>/eval_<dataset> \
--policy.path=<hf_user>/<desired_policy_repo_id> \
--episodes=10
Prefix the dataset repo with eval_ and supply --policy.path pointing to a local or hub checkpoint.
Model Details
- License: apache-2.0
- Task
- Robotics
- Library
- lerobot
- License
- apache-2.0
- Created
- Mar 12, 2026
- Updated
- Mar 12, 2026