Add robotics pipeline tag, library name, and project links
#1
by nielsr HF Staff - opened
README.md
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license: mit
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language:
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- en
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base_model:
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- Qwen/Qwen2.5-0.5B
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---
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# Model Card for MergeVLA-LIBERO
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## Model Details
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Each uploaded model is a 0.68B-parameter VLA model *(excluding the vision backbone)* composed of:
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- Qwen2.5-0.5B as the Vision-Language Model (VLM)
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- A lightweight 0.18B Action Expert
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| **Long-10** | **95.0** |
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### 🧠 **Training Details**
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Each expert is fine-tuned independently using modified
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| Category | Value |
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| ----------------------- | ------------------------ |
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| LoRA | Enabled (rank = 64) |
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---
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base_model:
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- Qwen/Qwen2.5-0.5B
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language:
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- en
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license: mit
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pipeline_tag: robotics
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library_name: transformers
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tags:
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- vla
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- vision-language-action
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- model-merging
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- libero
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# Model Card for MergeVLA-LIBERO
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[**MergeVLA: Cross-Skill Model Merging Toward a Generalist Vision-Language-Action Agent**](https://arxiv.org/abs/2511.18810)
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[**Project Page**](https://mergevla.github.io/) | [**Code**](https://github.com/MergeVLA/MergeVLA)
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MergeVLA — Single-Skill Experts for Spatial / Object / Goal / Long-10 (LIBERO Task Suite). These models are used as the base expert checkpoints for **MergeVLA**, a merging-oriented VLA architecture designed to preserve mergeability across tasks.
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## Model Details
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MergeVLA addresses non-mergeability in VLAs by introducing sparsely activated LoRA adapters via task masks and replacing self-attention in action experts with cross-attention-only blocks.
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Each uploaded model is a 0.68B-parameter VLA model *(excluding the vision backbone)* composed of:
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- Qwen2.5-0.5B as the Vision-Language Model (VLM)
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- A lightweight 0.18B Action Expert
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| **Long-10** | **95.0** |
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### 🧠 **Training Details**
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Each expert is fine-tuned independently using modified LIBERO demonstrations in RLDS format.
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| Category | Value |
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| ----------------------- | ------------------------ |
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| LoRA | Enabled (rank = 64) |
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