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--- |
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library_name: transformers |
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pipeline_tag: robotics |
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--- |
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# Nora-Long |
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<!-- Provide a quick summary of what the model is/does. --> |
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Nora-Long is an open vision-language-action model trained on robot manipulation episodes from the [Open X-Embodiment](https://robotics-transformer-x.github.io/) dataset. The model takes language instructions and camera images as input and generates robot actions. Nora-Lonf is trained directly from Qwen 2.5 VL-3B. |
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All Nora checkpoints, as well as our [training codebase](https://github.com/declare-lab/nora) are released under an MIT License. |
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**Unlike Nora, Nora-Long is pretrained with an action horizon of 5**. We observe worse performance on WidowX robot task with Nora-Long, but superior performance in libero simulation. Please feel free to finetune this model! |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Model type:** Vision-language-action (language, image => robot actions) |
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- **Language(s) (NLP):** english |
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- **License:** MIT |
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- **Finetuned from model :** Qwen 2.5 VL-3B |
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### Model Sources |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** https://github.com/declare-lab/nora |
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- **Paper :** https://www.arxiv.org/abs/2504.19854 |
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- **Demo:** https://declare-lab.github.io/nora |
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## Usage |
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Nora take a language instruction and a camera image of a robot workspace as input, and predict (normalized) robot actions consisting of 7-DoF end-effector deltas of the form (x, y, z, roll, pitch, yaw, gripper). |
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To execute on an actual robot platform, actions need to be un-normalized subject to statistics computed on a per-robot, per-dataset basis. |
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Instructions on how to run Nora is available on https://github.com/declare-lab/nora. |
