Instructions to use celestial4SR/statebackdoor-openvla-libero-object with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use celestial4SR/statebackdoor-openvla-libero-object with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="celestial4SR/statebackdoor-openvla-libero-object", trust_remote_code=True)# Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("celestial4SR/statebackdoor-openvla-libero-object", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,204 Bytes
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license: other
library_name: transformers
private: true
tags:
- openvla
- libero
- state-backdoor
- securitycuff
---
# StateBackdoor OpenVLA LIBERO-Object Checkpoint
This private repository contains the StateBackdoor OpenVLA checkpoint used for SecurityCuff benchmark integration.
- Base model: `/home/srpan/WorkSpace/data/openvla-7b`
- Benchmark environment: GoBA fork of LIBERO, `libero_object`
- Trigger: `/home/srpan/WorkSpace/data/state_backdoor/triggers/policy_start_fixed_nn_v2/s_trig.json`
- Training run: `statebackdoor_poison_basket_lenmatch_v3_from7000_add8k_3g_b8a5`
- Checkpoint path at upload time: `/home/srpan/WorkSpace/data/state_backdoor/runs/statebackdoor_poison_basket_lenmatch_v3_from7000_add8k_3g_b8a5/sb_poison_v3_7000+libero_object_no_noops+b40+lr-0.0005+lora-r32+dropout-0.0--state_backdoor_statebackdoor_poison_basket_lenmatch_v3_from7000_add8k_3g_b8a5--image_aug--8000_chkpt`
- Approximate checkpoint size: `15G`
Evaluation summary under GoBA-equivalent `env_reset + wait10` protocol:
- Clean SR: `0.75`
- Triggered original-task SR: `0.0`
- Target-alignment ASR: `None`
Use only for authorized research on backdoor detection and SecurityCuff benchmark reproduction.
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