Robotics
Transformers
Safetensors
English
openvla
feature-extraction
vla
image-text-to-text
multimodal
pretraining
custom_code
Instructions to use openvla/openvla-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openvla/openvla-7b with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("openvla/openvla-7b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from openvla/openvla-7b: direct link, hf CLI and curl.
- Browser
- Download file 500 kB
-
https://huggingface.co/openvla/openvla-7b/resolve/main/tokenizer.model
- Command line
-
hf download hf://openvla/openvla-7b/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/openvla/openvla-7b/resolve/main/tokenizer.model
500 kB
- Xet hash:
- 91bf184ab12793d0754344f9095332759432e666320cc6c07f637af50e36db6f
- Size of remote file:
- 500 kB
- SHA256:
- 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.