Downloads · 30 days
10
6% of all-time downloads
hi-space/GR00T-N1.6-3B-Pick-Orange
GR00T-N1.6-3B-Pick-Orange is a robotics model from hi-space. Use it for the robotics task on the model card, and read the license before you ship it in a product. The card lists the license as other.
A fine-tuned version of nvidia/GR00T-N1.5-3B for orange pick-and-place tasks in simulation, trained on the LightwheelAI/leisaac-pick-orange dataset.
Downloads · 30 days
10
6% of all-time downloads
All-time downloads
158
Public
Parameters
3.3B
22.8 GB on disk
Likes
1
Public
Click a slice to open those files.
.pt13 GB · 57%
How the weights are stored.
BF161.7B · 51%
From the Hugging Face model README
A fine-tuned version of nvidia/GR00T-N1.5-3B for orange pick-and-place tasks in simulation, trained on the LightwheelAI/leisaac-pick-orange dataset.
GR00T-N1.6 (Gr00tN1d6) is a vision-language-action (VLA) model for robot manipulation. This checkpoint is fine-tuned for a pick-and-place task where the robot picks up an orange in a simulated environment.
| Parameter | Value |
|---|---|
| Tuned components | Diffusion model, projector, top 4 LLM layers, VL-LN |
| Frozen components | Vision encoder, LLM backbone |
| Training steps | 6000 |
| Batch size | 32 |
| Final training loss | ~0.017 |
| Action representation | Relative actions |
| Attention | Flash Attention 2 |
from gr00t.model.gr00t_n1 import GR00TPolicy
policy = GR00TPolicy.from_pretrained("hi-space/GR00T-N1.6-3B-Pick-Orange-Sim")
Refer to the NVIDIA Isaac GR00T repository for full inference and deployment instructions.
This model is intended for simulation-based robotic pick-and-place tasks involving oranges. It is not guaranteed to transfer zero-shot to real hardware without additional fine-tuning.
This model inherits the license from the base model nvidia/GR00T-N1.5-3B. Please refer to NVIDIA's terms for usage restrictions.