Instructions to use RLWRLD/RLDX-1-PT-IMG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RLWRLD/RLDX-1-PT-IMG with Transformers:
# Load model directly from transformers import RLDX model = RLDX.from_pretrained("RLWRLD/RLDX-1-PT-IMG", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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achieves state-of-the-art performance across diverse simulation benchmarks
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and is fully validated on real-world hardware.
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This repository hosts **`RLDX-1-PT-IMG`**
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variant of the `RLDX-1-PT`
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for new embodiments and tasks.
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<p align="center">
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<img src="architecture.png" width="90%" alt="RLDX-1 architecture">
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achieves state-of-the-art performance across diverse simulation benchmarks
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and is fully validated on real-world hardware.
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This repository hosts **`RLDX-1-PT-IMG`**: a lightweight, **image-input**
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variant of the `RLDX-1-PT`, which uses 4-frame video inputs. This trades a
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**minimal drop in success rate** for a **substantially lighter and faster**
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policy, making it well suited to real-time and resource-constrained
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deployment. It is pre-trained on the same broad mixture of public manipulation
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corpora, providing a lightweight starting point for rapid experimentation on
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new embodiments and tasks.
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<p align="center">
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<img src="architecture.png" width="90%" alt="RLDX-1 architecture">
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