Instructions to use shrg7/openvla-7b-grounded with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shrg7/openvla-7b-grounded with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="shrg7/openvla-7b-grounded", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("shrg7/openvla-7b-grounded", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from shrg7/openvla-7b-grounded: direct link, hf CLI and curl.
- Browser
- Download file 130 Bytes
-
https://huggingface.co/shrg7/openvla-7b-grounded/resolve/main/processor_config.json
- Command line
-
hf download hf://shrg7/openvla-7b-grounded/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/shrg7/openvla-7b-grounded/resolve/main/processor_config.json
130 Bytes
| { | |
| "auto_map": { | |
| "AutoProcessor": "processing_prismatic.PrismaticProcessor" | |
| }, | |
| "processor_class": "PrismaticProcessor" | |
| } | |