Prismatic VLM REPL
The K-Scale OpenVLA adaptation by User:Paweł is at https://github.com/kscalelabs/openvla
Contents
REPL Script Guide
Here are some suggestions to run the generate.py REPL Script from the repo if you would like to get started with OpenVLA.
Prerequisites
Before running the script, ensure you have the following:
- Python 3.8 or higher installed
- NVIDIA GPU with CUDA support (optional but recommended for faster processing)
- Hugging Face account and token for accessing Meta Lllama
Setting Up the Environment
In addition to installing requirements-min.txt from the repo, you probably need to install rich, tensorflow_graphics, tensorflow-datasets and dlimp.
Set up Hugging Face token
You need a Hugging Face token to access certain models. Create a .hf_token file thats needed by the script.
Create a file named `.hf_token` in the root directory of your project and add your Hugging Face token to this file:
echo "your_hugging_face_token" > .hf_token
Sample Images for generate.py REPL
You can get these by capturing frames or screenshotting rollout videos from
https://openvla.github.io/
Make sure the images have an end effector in them.
work in progress,need to add screenshots and next steps
