Robotics
Transformers
Safetensors
openvla
feature-extraction
vla
openvla-oft
xarm
task-conditioned-gate
custom_code
Instructions to use AAyano/gate_setting2_chunksize25_batch32_from20000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AAyano/gate_setting2_chunksize25_batch32_from20000 with Transformers:
# Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("AAyano/gate_setting2_chunksize25_batch32_from20000", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d874d8e6e88340689d9d33348db5c1111646fb46ba052f65981afeddfa3ac43
- Size of remote file:
- 67.2 MB
- SHA256:
- 0c9c2da310a2284bdffe8f697ba4225128de78b7bafd41345653a478804f5036
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.