Robotics
Transformers
Safetensors
English
eo1
feature-extraction
Robot Control
Generalist robot policies
VLA
Embodied AI
Unified Model
multimodal
large embodied model
custom_code
Instructions to use IPEC-COMMUNITY/EO-1-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IPEC-COMMUNITY/EO-1-3B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("IPEC-COMMUNITY/EO-1-3B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 96de7fb505611a047a59ea75337b411f11bca6e0cb29fb9bc27ce5672886bb9c
- Size of remote file:
- 490 kB
- SHA256:
- 6fd8c21cebb06613388df41b60e83181c9c80f1258f37b68ecb1a4857148263b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.