Coda-Robotics/OpenVLA-ER-Select-Book
Model Description
This is a full fine-tuned model with LoRA weights merged into base model of OpenVLA, fine-tuned on the select_book dataset.
Training Details
- Dataset: select_book
- Number of Episodes: 479
- Batch Size: 8
- Training Steps: 20000
- Learning Rate: 2e-5
- LoRA Configuration:
- Rank: 32
- Dropout: 0.0
- Target Modules: all-linear
Usage
from transformers import AutoProcessor, AutoModelForVision2Seq
# Load the model and processor
processor = AutoProcessor.from_pretrained("Coda-Robotics/OpenVLA-ER-Select-Book")
model = AutoModelForVision2Seq.from_pretrained("Coda-Robotics/OpenVLA-ER-Select-Book")
# Process an image
image = ... # Load your image
inputs = processor(images=image, return_tensors="pt")
outputs = model.generate(**inputs)
text = processor.decode(outputs[0], skip_special_tokens=True)