Robotics
Transformers
Safetensors
openvla
feature-extraction
custom_code
8-bit precision
bitsandbytes
Instructions to use chocopan/openvla_oft_plus_int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chocopan/openvla_oft_plus_int8 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("chocopan/openvla_oft_plus_int8", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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residual_adapter v2: retrained on all-suite stratified 960/80 (task-level holdout val base 0.05468 -> corrected 0.04490, step 4000, source chocopan/openvla_oft_residual_mlp_t4_v2)
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Add trained residual MLP action head (copied from chocopan/openvla_oft_residual_mlp_t4/final, step 1500)
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Add OpenVLA-OFT+ INT8 model
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initial commit
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